Masterthesis Sameera

Communication NetworksUniversity of Bremen

Prof. Dr. rer. nat. habil. C. Görg

Master Thesis

A Scalable and Self-Sustained Femtocell

Architecture for LTE-A

of

Dhanapala M. S. Palipana

Matriculation Number: 2581426

Bremen, January 16th, 2014

Supervised by:Prof. Dr. rer. nat. habil. C. GörgDr.-Ing. Yasir ZakiDr.-Ing. Umar Toseef

This publication is meant for internal use only. All rights reserved. No liabilities withrespect to its content are accepted. No part of it may be reproduced, stored in a retrievalsystem, or transmitted, in any form or by any means, electronic, mechanical, photocopying,recording, or otherwise, without the prior written permission of the publisher.

I assure, that this work has been done solely by me without any further help from othersexcept for the o�cal support by the Chair of Communication Networks. The literatureused is listed completely in the bibliography.

Bremen, January 16th, 2014

(Dhanapala M. S. Palipana)

Acknowledgements

This thesis concludes my studies of the Master of Science degree in Communicationand Information Technology at University of Bremen, Germany. At this point my sinceredebt of gratitude goes to Prof. Görg for giving me the opportunity to write this MasterThesis and my Mini Project under her supervision and also for providing the opportunitiesto develop throughout my studies.

I am sincerely grateful to my supervisor Dr.- Ing. Yasir Zaki who motivated and helpedme throughout my thesis sharing his knowledge with me in many areas, for his valuableadvice, encouragement and patience. I would also give my thanks to Dr. Ing. UmarToseef who gave me valuable advice on the thesis direction and helped whenever I askedfor his expertise. I also appreciate the help from other researchers of the CommunicationNetworks department Dr.-Ing. Koojana Kuladinithi, Asanga Udugama M.Eng., Dr.-Ing.Andreas J. Könsgen, and Dipl.-Ing. Karl-Heinz Volk for the support they provided.

In addition, I would also express my gratitude to my friends for giving me a happy andwonderful life in Bremen. Finally, special thanks goes to my family, for their unconditionallove, patience and support.

Dhanapala M.S. Palipana

Bremen, 16.01. 2014

Dhanapala M. S. Palipana 1

2 Dhanapala M. S. Palipana

Abstract

The continuously growing number of mobile devices in terms of hardware and ap-plications augments the necessity for higher data rates and a larger capacity in wirelesscommunication networks. The Long Term Evolution-Advanced (LTE-A) standard was de-signed to provide these mobile users with a better throughput, coverage and a lower latency.Instead of providing any enhancements to the macro eNodeBs introduced by its predecessorLTE, the LTE-A standard introduced six new technologies to meet the above mentionedgoals such as Carrier Aggregation (CA), Heterogeneous Networks (HetNets), EnhancedMIMO (Multiple Input Multiple Output), Relay Nodes, Coordinated Multi-Point (CoMP)and Self-organizing networks (SONs).

This thesis studies a speci�c area in Heterogeneous Networks, the subject of femtocells.The aim of femtocells is to provide better indoor coverage so as to allow users to bene�tfrom higher data rates while reducing the load on the macro eNodeBs. However, thereis an issue with femtocells that may obstruct the performance of femto- and macrocellswhich is �interference�. As femtocells also use the same spectrum as the macrocells and thefemtocells are deployed without proper planning, interference from femtocells to macrocellsbecomes an issue here.

In this thesis, the interference from femtocells to macrocells is studied and two novelsolutions for the mitigation of this kind of interference are provided, the �Home eNodeB(HeNB) Power Control� scheme and the �Random PRB Selection� scheme. The �rstmethod utilizes an analytical approach to mitigate interference based on Channel QualityIndicator (CQI) reports from macrocell users. The other method uses a more simple ap-proach and chooses a random subset of Physical Resource Blocks (PRBs) to allocate toHeNB users so that macrocell users will bene�t from a reduced interference level and alarger range of PRBs.

The implementation and simulation of the proposed schemes are carried out using theComNets LTE-A system level simulator in OPNET Modeler software. The results indicatethat the two schemes alleviate the macrocell interference signi�cantly with respect to Signalto Interference and Noise Ratio (SINR) and the performance of user applications. TheHeNB Power Control scheme performs as a balanced scheme which mitigates the macrocelluser interference e�ectively while securing a better throughput for the HeNB users. Incontrast, the Random PRB Selection scheme performs exceptionally well regarding themacrocell user interference mitigation with a slight diminished performance for the homeusers.


Kurzfassung

Die ständig zunehmende Anzahl an mobilen Endgeräten und Anwendungen verstärktdie Notwendigkeit für höhere Datenraten und mehr Kapazität in drahtlosen Kommuni-kationsnetzen. Der Long Term Evolution-Advanced (LTE-A)-Standard wurde entworfen,um für diese mobilen Nutzer besseren Durchsatz, gröÿere Abdeckung und geringere Latenzzu ermöglichen. Anstelle der Verbesserung der Makro-eNodeBs, die durch den VorgängerLTE eingeführt wurden, führte der LTE-A-Standard zur Erreichung der Ziele sechs neueTechnologien ein wie Träger-Aggregierung (Carrier Aggregation, CA), Heterogene Netze(HetNets), verbessertes MIMO (Multiple Input Multiple Output), Relaisknoten, koordi-nierte Multipoints (CoMP) und selbstorganisierende Netze (SON).

Diese Arbeit befasst sich innerhalb des Bereiches heterogener Netze mit dem Themader Femtozellen. Der Zweck von Femtozellen ist, eine bessere Abdeckung im Innenbe-rich zu erzielen, um Benutzern eine höhere Datenrate bei Verringerung der Last für dieMakro-eNodeBs zu ermöglichen. Es gibt jedoch einen E�ekt bei Femtozellen, die die Lei-stungsfähigkeit von Femto- und Makrozellen verringern kann, nämlich die Interferenz. DaFemtozellen dasselbe Spektrum wie die Makrozellen verwenden und die Femtozellen ohnesorgfältige Planung eingerichtet werden, kann die Interferenz zwischen Femto- und Makro-zellen wesentlich sein.

In dieser Arbeit wird die Interferenz von Femtozellen zu Makrozellen untersucht undzwei neuartige Lösungen zur Abschwächung dieser Art von Interferenz werden vorgestellt,das �Home eNodeB (HeNB)-Leistungsregelungsverfahren� und das�PRB-Zufallsauswahlverfahren�. Die erste Methode verwendet einen analytischen Ansatzzur Verminderung der Interferenz basierend auf Kanalqualitäts-Indikator-Berichten (Chan-nel Quality Indicator, CQI) von Benutzern der Makrozelle. Das andere Verfahren verwen-det einen einfacheren Ansatz und verwendet eine zufällige Untermenge von physikalischenRessourcen-Blöcken (PRBs) für die Zuweisung an HeNB-Nutzer, so dass Makrozellen-Benutzer von einem verringerten Interferenz-Niveau und einer gröÿeren Reichweite derPRBs pro�tieren.

Die Implementierung und Simulation der vorgeschlagenen Verfahren werden mit demComNets LTE-A-Systemsimulator in der OPNET Modeler-Software durchgeführt. DieErgebnisse zeigen, dass die beiden Verfahren die Makrozellen-Interferenz signi�kant redu-zieren, bezogen auf das Signal-zu-Stör-und-Rausch-Verhältnis (Signal to Interference andNoise Ratio, SINR) und das Leistungsverhalten der Nutzeranwendungen. Das HeNB-Leistungsregelungsverfahren verhält sich als ein ausgewogenes Verfahren, das die Interfe-renz für die Makrozellen-Nutzer e�ektiv reduziert und gleichzeitg einen besseren Durchsatzfür die HeNB-Nutzer erzielt. Im Gegensatz dazu verhält sich dasPRB-Zufallsauswahlsverfahren auÿerordentlich gut bei der Verringerung der Interferenzbei den Makrozellen-Nutzern mit einem leicht verschlechterten Leistungsverhalten bei denHeimbenutzern.


Contents

Acknowledgements 1

Abstract 3

Kurzfassung 5

List of Figures 9

List of Tables 11

List of Abbreviations 13

1 Introduction 15

1.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161.3 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2 Overview on Femtocells 19

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.2 LTE-Advanced (LTE-A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2.2.1 Carrier Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.2.2 Multiple-Input, Multiple-Output (MIMO) . . . . . . . . . . . . . . . 212.2.3 Heterogeneous networks (HetNets) . . . . . . . . . . . . . . . . . . . 212.2.4 Relay Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212.2.5 Coordinated multipoint (CoMP) . . . . . . . . . . . . . . . . . . . . 242.2.6 Self-organizing networks (SONs) . . . . . . . . . . . . . . . . . . . . 24

2.3 Femtocell Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242.4 HeNB Protocol Stack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262.5 Requirements for the Functionality of HeNBs . . . . . . . . . . . . . . . . . 272.6 Bene�ts and Challenges for Femtocells . . . . . . . . . . . . . . . . . . . . . 29

2.6.1 Advantages for users . . . . . . . . . . . . . . . . . . . . . . . . . . . 292.6.2 Advantages for operators . . . . . . . . . . . . . . . . . . . . . . . . . 302.6.3 Disadvantages of having femtocells . . . . . . . . . . . . . . . . . . . 30

2.7 The Interference Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312.8 Intercell Interference Coordination (ICIC) . . . . . . . . . . . . . . . . . . . 31

2.8.1 HeNB Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . 322.8.2 Information Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . 342.8.3 Interference Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

2.8.3.1 Power Control Methods . . . . . . . . . . . . . . . . . . . . 352.8.3.2 Resource Partitioning . . . . . . . . . . . . . . . . . . . . . 36

3 Scalable and Self-sustained Femtocell Architecture 39

3.1 CQI Reporting in LTE-A . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.1.1 EESM SINR Calculation . . . . . . . . . . . . . . . . . . . . . . . . . 39

3.2 HeNB Power Control Scheme: The Analytical Approach Based on CQI Signals 413.2.1 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.2.1.1 HeNB Position Estimation . . . . . . . . . . . . . . . . . . 41

Contents

3.2.1.2 Wall Penetration Loss Estimation by the HeNB . . . . . . . 413.2.1.3 Estimation of Path Loss between HeNB and the MUE . . . 413.2.1.4 Detection of an A�ected MUE . . . . . . . . . . . . . . . . 423.2.1.5 Estimation of Fading and Noise at the MUE . . . . . . . . 42

3.2.2 Interference Mitigation Methodology . . . . . . . . . . . . . . . . . . 443.3 Random PRB Allocation Scheme . . . . . . . . . . . . . . . . . . . . . . . . 463.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

4 Channel and Mobility Models 494.1 Signal Propagation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494.2 Path Loss Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.3 Slow Fading Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514.4 Fast Fading Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554.5 Signal to Interference and Noise Ratio (SINR) . . . . . . . . . . . . . . . . . 56

4.5.1 SINR Calculation for a HeNB UE . . . . . . . . . . . . . . . . . . . . 564.5.2 SINR Calculation for a eNodeB UE . . . . . . . . . . . . . . . . . . . 56

4.6 Link to System Level Mapping . . . . . . . . . . . . . . . . . . . . . . . . . 574.7 The Mobility Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

5 Simulation Environment 615.1 Simulator Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 615.2 The Node Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 615.3 The Process Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

6 Simulation Results and Analysis 676.1 Simulation Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

6.1.1 FTP Tra�c Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 696.1.2 VoIP Tra�c Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 696.1.3 Video Tra�c Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

6.2 Simulation Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 706.3 Statistical Evaluation of Simulation Results . . . . . . . . . . . . . . . . . . 716.4 Results Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

6.4.1 VoIP User Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 746.4.2 FTP User Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 776.4.3 Video User Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 786.4.4 Throughput comparison of HeNB users . . . . . . . . . . . . . . . . . 796.4.5 Behavior of HeNB Power Control Scheme near to the eNodeB . . . 80

6.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

7 Conclusions and Future Work 857.1 Outlook and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 857.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

Bibliography 87


List of Figures

2.1 Overview of LTE-Advanced (3GPP Release 10) main features [1] . . . . . . 202.2 Component carrier aggregation (i) Intra-band contiguous (ii) Intra-band no-

contiguous (iii) Inter-band non-contiguous . . . . . . . . . . . . . . . . . . . 222.3 An overview of a heterogeneous network [2] . . . . . . . . . . . . . . . . . . 232.4 3GPP relay architecture and interfaces [1] . . . . . . . . . . . . . . . . . . . 232.5 3GPP femtocell architecture overview . . . . . . . . . . . . . . . . . . . . . 252.6 Protocol Stack- User plane without an HeNB Gateway . . . . . . . . . . . . 272.7 Protocol Stack- Control plane without an HeNB gateway . . . . . . . . . . . 282.8 EUTRAN protocol stack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282.9 Colayer interference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322.10 Crosslayer interference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322.11 An example component carier aggregation scenario . . . . . . . . . . . . . . 372.12 An example ABS scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

3.1 Estimation of MUE path loss . . . . . . . . . . . . . . . . . . . . . . . . . . 433.2 Random PRB Selection Scheme in a bloack diagram . . . . . . . . . . . . . 47

4.1 Multipath, Shadowing and Path Loss Against Distance [3] . . . . . . . . . . 504.2 Path Loss Map for a 100m × 100m Area . . . . . . . . . . . . . . . . . . . . 524.3 A Simpli�ed Example of Generating Correlated Slow Fading Values . . . . . 534.4 Generating a correlated 2D slow fading map using 5 neighboring points . . . 544.5 A 100m× 100m Correlated Slow Fading Map for a HeNB with mean 0 and

std. dev. 4dB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 544.6 Fast Fading Map for a HeNB UE with 3kmph speed having the PedB channel

model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554.7 AWGN Channel BLER vs. SINR Curve [4] . . . . . . . . . . . . . . . . . . 584.8 Mobility Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

5.1 OPNET Modeler environment . . . . . . . . . . . . . . . . . . . . . . . . . . 625.2 Simulation Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635.3 eNodeB and HeNB Node Model . . . . . . . . . . . . . . . . . . . . . . . . 645.4 eNodeB and HeNB MAC Layer Process Model . . . . . . . . . . . . . . . . 645.5 Global UE List Process Model . . . . . . . . . . . . . . . . . . . . . . . . . 65

6.1 Simulation Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686.2 HenB Positions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686.3 MOS values vs End to end delay of VoIP users [4] . . . . . . . . . . . . . . . 726.4 PDF of the Student's t distribution with con�dence interval and con�dence

level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 736.5 SINR, end-to-end delay and MOS values of VoIP users . . . . . . . . . . . . 766.6 SINR and download response time values of FTP users . . . . . . . . . . . . 786.7 SINR and end-to-end delay values of video users . . . . . . . . . . . . . . . 796.8 �g:HUE's PRB usage and throughput comparison . . . . . . . . . . . . . . . 806.9 Macro UE path plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

List of Figures


List of Tables

2.1 No. of PRBs and the respective bandwidth of a component carrier . . . . . 202.2 Interference Scenarios [5] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312.3 Measurements from all cells [6] . . . . . . . . . . . . . . . . . . . . . . . . . 322.5 HeNB Measurements from surrounding macro cells [6] . . . . . . . . . . . . 332.4 HeNB measurements from surrounding cells [6] . . . . . . . . . . . . . . . . 332.6 HeNB measurements from adjacent HeNBs [6] . . . . . . . . . . . . . . . . . 34

3.1 CQI vs MCS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403.2 β values for each MCS [7], [8] . . . . . . . . . . . . . . . . . . . . . . . . . . 40

4.1 ITU Channel Model for PedB . . . . . . . . . . . . . . . . . . . . . . . . . . 55

6.1 Simulation Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 696.2 FTP Tra�c Model Parameters . . . . . . . . . . . . . . . . . . . . . . . . . 706.3 VoIP Tra�c Model Parameters . . . . . . . . . . . . . . . . . . . . . . . . . 706.4 Video Streaming Model Parameters . . . . . . . . . . . . . . . . . . . . . . . 706.5 Scenarios types used in the simulations and the terms used for them . . . . 71

List of Tables


List of Abbreviations

3GPP 3rd Generation Partnership Project

3GPP2 3rd Generation Partnership Project2

ADSL Asymmetric Digital Subscriber Line

BLER Block Error Rate

CoMP Coordinated Multi-Point

CRS Common Reference Signal

CQI Channel Quality Indicator

eICIC Enhanced Intercell InterferenceCoordination

eNodeB Evolved NodeB

EPC Evolved Packet Core

EESM Exponential E�ective SINRMapping

E-UTRAN Evolved Universal Terrestrial RadioAccess Network

GSM Global System for MobileCommunications

HARQ Hybrid Automatic Repeat Request

HeNB Home Evolved NodeB

HUE Home User Equipment

HSS Home Subscriber Service

HII High Interference Indicator

ICIC Intercell Interference Coordination

IP Internet Protocol

LTE Long Term Evolution

LTE-A Long Term Evolution-Advanced

MAC Medium Access Control

MCS Modulation and Coding Scheme

MME Mobility Management Entity

MOS Mean Opinion Score

MUE Macro User Equipment

MU-MIMO Multiuser Multiple Input-MultipleOutput

NAS Non Access Stratum

NLM Network Listen Mode

OI Overload Indicator

OFDMA Orthogonal frequency divisionmultiple access

PBCH Physical broadcast channel

PDCCH Physical Downlink Control Channel

PDCP Packet Data Control Protocol

PDU Protocol data Unit

PedB Pedestrian B

P-GW Packet Data Network Gateway

PRB Physical Resource Block

RLC Radio Link Control

RNTP Relative Narrowband TransmitPower

RRC Radio Resource Control

RSRP Reference Signal Received Power

S1-AP S1 Application Protocol

SC-FDMA Single Carrier Frequency DivisionMultiple Access

SCTP Stream Control TransmissionProtocol

SDU Service data unit

SGSN Serving GPRS Support Node

S-GW Serving Gateway

SIB System Information Block

SU-MIMO Single User Multiple Input-MultipleOutput

TTI Transmission Time Interval

TSG-RAN Technical Speci�cation Group -Radio Access Network

UE User Equipment

UM Unacknowledged Mode

UMTS Universal MobileTelecommunications System

WiMAX Worldwide Interoperability forMicrowave Access

List of Abbreviations


1 Introduction

Cellular phones play a dominant part in modern day life. Nowadays it's very uncommonto see a person without access to a mobile phone. Latest facts from ITU [9] reveal that

by the end of 2013 there are 6.8 billion mobile phone users and by 2014 this will exceedthe world population. Since the introduction of smart phones in early 2000s the numberof online users have grown rapidly and with that the data rates in cellular networks haveincreased to greater proportions.

What these trends indicate is whilst network penetration is spreading to every partof the earth, mobile phone and internet is becoming more and more a�ordable to thecommoner. With these technological advancements arises the need to increase networkcapacity and speed. As the number of subscribers increases and data rate demand rises,traditional macrocells �nd it di�cult to make demands meet specially in densely populatedplaces.

In 2008 the Long Term Evolution (LTE) was introduced to cater these needs andwith that the femtocell concept was introduced. As a result of this, in a cellular networka mixture of macro and other smaller cells, such as pico and femto cells, are expected tocoexist in future. These new cells provide the network the capability to provide satisfactoryservices to places having high load, specially in densely populated areas and also to celledges where signal strength from macrocells can be low. But there are some adverse e�ectsthat can arise because of this coexistence. As an example, interference among di�erentcells can occur, specially among femtocells and macrocells because femtocells use the samespectrum used by macrocells and cell planning is also not performed like in picocells. This isalso called intercell interference. The main reason for unplanned deployment of femtocellsis that they are installed by home users, not the network operator.

With the standardization of LTE Advanced (LTE-A) in March 2011 coexistence ofdi�erent types of cells was de�ned as a heterogeneous network. Enhanced Intercell Inter-ference Coordination (eICIC) was newly introduced with LTE-A among other new featureswhich tries to tackle the problem of intercell interference. But this still remains as an openarea for further research since eICIC doesn't solve the problem entirely as of yet.

1.1 Related Work

After the standardization of femtocells by the 3rd Generation Partnership Project(3GPP) in 2009 there has been some extensive research done in the area of interferencefrom femtocells in the downlink. Standardization bodies like 3GPP Technical Speci�cationGroup for Radio Access Networks (TSG-RAN) Work Group 4 (WG4) has also looked intointerference reduction methods for Long Term Evolution (LTE) [6]. All the methods theyhave proposed for the downlink data channel protection can be divided into two areas,power control and radio resource management. Radio resource management in LTE-Ainvolves component carrier aggregation, almost blank subframes and resource partitioningwith resource blocks which will be further elaborated in chapter 2. In the next paragraphother important work on power control will be listed followed by resource partitioningmethods.

Claussen et al. [10] introduced a method, instead of using �xed power levels a HeNBcan con�gure the transmit power based on the measured signal level from the eNodeB.Morita et al. [11] developed a scheme that estimates the path loss between the HeNBand the eNodeB based on the received power levels from the neighboring macrocell UEs.

1. Introduction

They extended this scheme to an auto-tuning scheme of the power o�set adaptive to thevarious interference conditions such as the size of buildings where the HeNB UEs exist anddistance to a street where eNodeB UEs exist [12]. But the drawback of these two methodsis that they rely on accurate estimation of path loss from the eNodeB based on referencesignal received power. Received strength of the reference signal can be erroneous becauseof fading that is inherent in it and as a result path loss estimation also becomes inaccurate.Arauz et al. proposed a method that employs distributed cooperative control theory toenable self organization of femtocell transmitters to mitigate interference via power control[13]. But this method requires backhaul link communication among HeNBs to manageinterference collectively which can be delay prone because interference mitigation requireslatencies of milliseconds although backhaul links are able to provide latencies in tens ofmilliseconds.

A dynamic resource partitioning method that denies HeNBs to access downlink re-sources that are assigned to macro UEs in their vicinity was introduced by Bharucha etal. [14]. Through this way most vulnerable macro UEs can be e�ectively controlled atthe expense of femtocell capacity. But the drawback is, this method requires an X2 link,which is an interface used by neighboring eNodeBs for communication among each otherin LTE-A. But 3GPP has discontinued the support of X2 interface for HeNBs in its latestreleases. In [15] a new intercell interference avoidance method based on resource partition-ing was proposed that does not require the X2 interface or over the air signaling. In thismethod the eNodeB schedules the UEs a�ected by HeNBs to a special part of the spectrumsuch that the HeNBs map the downlink resource blocks from uplink sensing. Furthermore,they divided this method into two, carrier aggregation approach and resource partitioningapproach. But the problems lies at the uplink to downlink Resource Block mapping that'sperformed by the HeNB which implies that the mapping scheme must be exchanged amongthe eNodeBs and HeNBs.

A method that involves resource partitioning and power allocation on the basis oflocal information such as user required rate, desired signal quality, level of interference andthe amount of fading in each resource block that's available at the HeNB was introducedin [16]. These inputs are used in a fuzzy inference system to control the allocation ofresource blocks to the users and change the transmit power levels. [17] describes a methodwhich measures the interference values of each RB at the HeNB location and computes aninterference cartography diagram for the HeNB coverage area, then it classi�es the RBsand allocates them to the appropriate users with suitable transmit powers. But thesemethods are computationally intensive and are not suitable for femtocell networks.

[18] describes an interference mitigation scheme for macro users with time domainmuting where the macro users in a coverage hole are protected by scheduling them only onthe muted subframes that are free of HeNB interference. It has also considered di�erentmethods for coverage hole detection. But the drawback of this method is that it wastesresources by scheduling macro users in muted subframes and if these macro users requirehigher data rates this scheme is not able to satisfy them.

1.2 Problem Statement

This thesis aims at studying the impact of femtocells on the macro and femto UserEquipment (UEs) and the operator network. It introduces two solutions that try to addressthe interference problem from femtocells to macro UEs.

The �rst method, �HeNB Power Control� scheme is an analytical solution which adaptsthe femtocell transmit power based on the Channel Quality Indicator (CQI) signals fromthe nearest a�ected UE. Here the femtocell tries to minimize its e�ect on the macro UE


1.3. Thesis Overview

throughout the time that it is in the HeNB's interfering area based on the macro UE CQIvalue that it sends in the uplink. The second method, �Random PRB Selection� schemeis a randomized frequency hopping technique where the macro UEs are scheduled in asubset of random PRBs in order to reduce the overall interference on the macro UEs. Thebehavior of femtocell interference is compared among these two methods in terms of theuser throughput, Exponential E�ective SINR Mapping (EESM), and overall packet delaysetc., using the LTE-A Comnets System Level Simulator [4], [19], [20], [21] developed inOPNET Modeler 17.5.

Two separate mobility models are used for both femto and macro UEs where the femtousers travel only inside a 15m × 15m house at the pedestrian speed and the macro userstravel inside the macrocell coverage area at pedestrian and vehicular speeds. Both typesof users are a�ected by white noise, path loss, slow fading with spatial correlation, fastfading and interference from other eNodeBs.

1.3 Thesis Overview

The rest of the thesis is organized as follows: Chapter 2 gives an overview of thefemtocells and gives an introduction to its current standardization environment LTE Ad-vanced which is also known as 3GPP Rel. 10. Chapter 3 discusses the two interferencemitigation schemes introduced by this thesis. Chapter 4 gives a description on the channelmodel, mobility model and link to system level mapping that is used by this thesis work.The next chapter explains the simulation environment of the OPNET modeler and theComnets LTE-A system level simulator. Chapter 6 evaluates the simulation results andthe �nal chapter presents the conclusions and also gives a brief description on how thiswork can be extended for further enhancements.


1. Introduction


2 Overview on Femtocells

2.1 Introduction

Femtocells are small, low power, low cost, short ranged and plug and play cellularbase stations that can be placed inside homes and can be directly connected to the

backhaul network through Internet Protocol (IP). By means of a network connection suchas Asymmetric Digital Subscriber Line (ADSL) or through optical �ber this backhaulconnection can be established. From the user's point of view these are plug and playdevices and no prior technical knowledge about the installation is required. However thesedevices have to be purchased from the mobile network operator by anyone wishing to haveit in their residences. The advantages of having a femtocell are that the indoor coverage canbe enhanced, coverage holes can be eliminated and also the operators can provide a betterservice at the cell edge. A detailed description about the advantages and disadvantages ofhaving a femtocell are given in the section 2.6.

Femtocells are also called HeNBs or simply Femto base stations and it's a subsetof a larger group called smallcells. Other types of base stations de�ned by 3GPP are�Macro base stations� for wide area coverage, medium range base stations called �Microbase stations� and local area base stations called �Pico base stations� for the coverageof large buildings like shopping malls and supermarkets. But the main advantage of afemtocells over picocells is their a�ordability for domestic use like Wi-Fi hotspots.

There are currently three organizations working on the standardization of the femto-cells, 3GPP, Smallcell Forum and Broadband Forum. The industry and the universities arealso cooperating with them in the standardization process. As this thesis is based on the3GPP Rel. 10 standardization for femtocells, which is also called LTE Advanced (LTE-A),in the following section a brief introduction on LTE-A and its new features is given.

2.2 LTE-Advanced (LTE-A)

As mentioned in section 1.1 femtocells were �rst standardized in 2009 by the 3GPP.The initial standard formed parts of 3GPP's Release 8 and was interdependent with Broad-band Forum extensions to its Technical Report-069 (TR-069) [22]. It was further enhancedby the introduction of heterogeneous networks for the co-channel deployment of macrocellsand smallcells in 3GPP Release 10. Instead of providing any enhancements to the macrobase stations, the focus of LTE-A has been to come up with new technologies and featuresfor LTE in order to provide several bene�ts for the users and the operators in terms ofincreased throughput, capacity and coverage. Figure 2.1 illustrates the main features andtheir bene�ts with regards to this release.

2.2.1 Carrier Aggregation

Carrier Aggregation is a method used by 3GPP Rel. 10 to increase the user data ratesand throughput via the increase of the bandwidth. By combining a maximum of 5 LTERel. 8 component carriers each having up to 20MHz of bandwidth, a combined maximumbandwidth up to 100 MHz can be achieved. The allowed bandwidths for a componentcarrier are 1.4MHz, 3.0 MHz, 5 MHz, 10 MHz, 15 MHz and 20 MHz. As the componentcarrier bandwidth increases, the amount of used Physical Resource Blocks (PRBs) alsoincrease. Table 2.1 gives the relationship between the number of PRBs and the componentcarrier bandwidth.

2. Overview on Femtocells

Carrier aggregation

Multiple input,

multiple output

Heterogeneous

networks

Relays

Coordinated

multipoint

Self-organizing

networks

Higher data rates

Higher spectral

efficiency

Simple addition of

small cells

Coverage

enhancements

Multicell transmissions

Simplified operations

Figure 2.1: Overview of LTE-Advanced (3GPP Release 10) main features [1]

Bandwidth (MHz) No. of resource blocks1.4 63 155 2510 5015 7520 100

Table 2.1: No. of PRBs and the respective bandwidth of a component carrier


2.2. LTE-Advanced (LTE-A)

Regarding peak data rates and spectrum e�ciency, carrier aggregation performs al-most similar to that of single carrier spectrum allocation. But it also provides the addedadvantage of inter-band and intra-band contiguous and non-contiguous spectrum alloca-tions as shown in the �gure 2.2. As component carrier aggregation can also be deployed byheterogeneous networks having macrocells and femtocells, this provides a �exible frequencyreusing scheme that reduces interference among them without limiting the user data rates.

2.2.2 Multiple-Input, Multiple-Output (MIMO)

MIMO is one of the key technologies used in modern mobile communication. It usesmultiple antennas in both the transmitter and receiver sides with the aim of increasingthe throughput. MIMO can have upto 8 × 8 antennas in the downlink and 4 × 4 inthe uplink with eight parallel data streams in the downlink and four in the uplink inLTE-A. Along with beamforming, multiple antennas increase the user data rates and thenetwork capacity. When the transmissions are for a single user, it is called Single-UserMIMO (SU-MIMO) and for multiple users it is Multi-User MIMO (MU-MIMO). SU-MIMOsigni�cantly improves the user throughput if the receiver also has multiple antennas and inMU-MIMO a transmitter can use the same frequency to transmit to di�erent users utilizingthe spatial separation. This way it improves the spectral e�ciency.

2.2.3 Heterogeneous networks (HetNets)

A Heterogeneous network refers to the co-channel deployment of macrocells and smallcells with the purpose of increasing the network capacity and coverage and also to removecoverage holes in indoor and outdoor areas. Small cells here mainly refer to picocells,femtocells, distributed antennas and relays. Picocells are well suited for shopping mallsand large o�ce buildings and they enhance the coverage in such places.

Distributed antennas provide a uniform quality of service over the total coverage areaalthough they don't increase the capacity. They just share the same resources in the airinterface in a large coverage area. The advantage of having distributed antennas is that thesystem can be upgraded easily by plugging in a new base station and distributed antennassimply extend the base station's antenna ports. A description on relays is provided in thesection 2.2.4. The main advantage of femtocells over picocells and distributed antennas isthat they do not need to be carefully planned.

One of the most important aspects in heterogeneous networks is cross-layer interferencewhich is more relevant to femtocells. This topic is elaborated more on section 2.7.Figure 2.3illustrates an overview of a heterogeneous network comprising of all the above mentionedtechnologies.

2.2.4 Relay Nodes

Relay nodes is a technology used to backhaul macrocells through the same LTE radiointerface and here the macrocell behaves as a donor eNodeB. Figure 2.4 explains how therelay concept works. From the view of the core network the relay behaves as another sectorin the donor eNodeB and from the perspective of the neighboring cells the UE connectedto a relay is seen as a UE connected to the donor eNodeB. Having relay nodes result in awider network coverage to places where providing backhaul connections through wires isdi�cult and it also reduces infrastructure costs for wired backhaul links.



(i)

(ii)

(iii)

Frequency Band AFrequency

Band B

Frequency Band A

Frequency Band A

Frequency

Band B

Frequency

Band B

Figure 2.2: Component carrier aggregation (i) Intra-band contiguous (ii) Intra-band no-contiguous (iii) Inter-band non-contiguous


2.2. LTE-Advanced (LTE-A)

Picocell

Femtocell

Relay

RF LinkBackhaul

Link

Distributed

AntennasInternet

Core

Network

ADSL or

Fiber Optic

Figure 2.3: An overview of a heterogeneous network [2]

Relay Node Donor eNodeB

eNodeB

UEMME/S-GW

MME/S-GW

Uu Uu

S1

S1

S1S1

X2

Figure 2.4: 3GPP relay architecture and interfaces [1]



2.2.5 Coordinated multipoint (CoMP)

CoMP is a method used to increase the cell edge throughput that usually gets limiteddue to intercell interference. This allows a user equipment to receive data from severaleNodeBs because the macrocells distributed around the cell edge area cooperate with oneanother to achieve a better signal quality to the user. Because of this, CoMP has theadvantages of improving the coverage while achieving high data rates as well as increasingthe cell edge throughput.

LTE-A speci�es di�erent techniques for CoMP in both the downlink and the uplink.In the downlink, Joint Processing and Coordinated Scheduling can be used and in JointProcessing, several eNodeBs transmit at the same time to the same UE. In coordinatedScheduling, only the serving eNodeB transmits data to the a�ected UE. In the uplink JointReception is one CoMP technique that's speci�ed. Here the transmissions of the UE isreceived simultaneously by some or all the cooperating eNodeBs and this can be used withinter point processing to increase the received signal quality.

2.2.6 Self-organizing networks (SONs)

Self-organizing networks help the network to operate much faster and simpler in areassuch as planning, con�guration and optimization. Their purpose is to increase the per-formance of the network, reduce operating expenses and improve network resource usage.There are three architectural types of SONs: distributed, centralized and hybrid. In dis-tributed SONs the functions are distributed among eNodeBs at the edge of the network.In centralized SONs functions are centralized among higher order network elements of thenetwork. Hybrid SON combines the functionality of distributed and centralized SONs.

2.3 Femtocell Architecture

The femtocell architecture gives details on connections and interfaces of HeNBs toUEs, Evolved-Universal Terrestrial Radio Access Network (E-UTRAN) and core networkequipment. Figure 2.5 explains the femtocell architecture in detail which has similarities toconnections in the eNodeB architecture. Uu interface represents the air interface between aHeNB and UEs. The S1 interface from the HeNB is connected through a broadband accessgateway which is operated by the ISP to security gateway. S1 interface also exists amongHeNB-core network, HeNB Gateway-core network and eNodeB-core network connections.

In Evolved Packet Core (EPC) all HeNBs are connected to the Mobility ManagementEntity (MME) through a HeNB Gateway. This connectivity supports a large number ofHeNBs in a scalable way although directly connecting a HeNB to a MME is also allowedby 3GPP. A HeNB Gateway is seen by the MME as a HeNB and a HeNB sees it as aMME. The functions of a HeNB are similar to those of an eNodeB except in two occasions[23], when a HeNB Gateway connects to the HeNB and when a HeNB has Local IP Access(this is explained in detail in section 2.5). The procedures followed between the HeNB andEPC are also similar to those followed between an eNodeB and the EPC [23].

EPC consist of MMEs, Serving Gateways (S-GW), Packet Data network Gateways(P-GW), Home Subscriber Service(HSS), Security Gateways and HeNB Gateways. A briefdescription on the functionality of these entities is given below as these connections arecommon to both eNodeBs and HeNBs.

• Serving Gateway (S-GW)

S1 interfaces from eNodeBs connect to a MME and it acts as a separation point be-tween the core network and the radio access network. Its main function is to manage


2.3. Femtocell Architecture

SGiX2

Uu

Home UE

HeNB

Broadband IP Access

Security Gateway

HeNB Gateway

Macro UE

eNB

Uu eNB

S6a

S5MME/S-GWS1

P-GW

HSS

S1-U/S1-MME

Operator’s IP Services

S1Broadband

Access Gateway

E-UTRAN EPC

Figure 2.5: 3GPP femtocell architecture overview

the mobility of the users during handovers between eNodeBs and it also serves as theanchor for mobility between LTE and other technologies such as GSM and UMTS.Serving Gateway also routes and forwards data packets of .When a UE is idle, sendingdata in the downlink to that UE is terminated by the S-GW and if data arrives againto the same UE, paging is triggered. Paging messages are usually used to inform theidle users about a system information change.

• Mobility Management Entity (MME)

MME performs tasks such as the management of UE access to networks, assigningnetwork resources and managing mobility states for paging, handovers and roamingthrough the use of signaling and control functions. All control plane functions thatare related to subscribers are performed by the MME. It performs bearer activa-tion/deactivation functions such as security procedures, terminal to network sessionhandling and idle terminal location management. It also performs authentication ofa user with the help of a HSS because S6a interface is connected from HSS to MME.Non Access Stratum Signaling (NAS) ends at the MME and it also generates andallocates temporary identities to UEs. MME also provides mobility between LTEand other 3GPP technologies.

• Packet Data Network Gateway (P-GW)

Like S-GW, PDN gateway also facilitates connectivity of UEs to external packet datanetworks and behaves as a termination point of the packet data interface. It connectsto the S-GW through S5 interface. UEs can access several packet data networksthrough several PDN gateways. The P-GW also performs policy enforcement such asoperator speci�ed rules for allocation of resources, �ltering of packets for each user,as an example for detecting the application type, charging support and lawful inter-ception. P-GW also acts as the anchor for mobility between 3GPP and other non3GPP technologies such as WiMAX and 3GPP2.



• Home Subscriber Server (HSS)HSS is a database that keeps data related to users and subscribers and it is anextension of Home Location Register in pre-3GPP Release 4 and the AuthenticationCentre. It also provides support for mobility management, call and session setup,authentication of users and authorization of their access.

2.4 HeNB Protocol Stack

Protocol stack of a HeNB is similar to the protocol stack of an eNodeB. The interfacesalso remain the same unless a HeNB is connected to a HeNB-Gateway. The radio protocolarchitecture of an eNodeB in general can be divided into two planes as control plane anduser plane. User plane is responsible for handling data that's generated at the applicationlayer and control plane is responsible for handling signaling messages that are createdat the Radio Resource Control (RRC) layer. Figures 2.6 and 2.7 present user plane andcontrol plane protocol layers and interfaces respectively.

Figure 2.6 illustrates the user plane protocol layers and interfaces that exist among theUE, HeNB, S-GW and the P-GW. L1 of both the UE and the HeNB interface is the PhysicalLayer which is at the bottom of the protocol stack and it takes all the information comingfrom the MAC transport channels through air interface in the form of physical channels.The multiple access scheme at the downlink is Orthogonal Frequency Division MultipleAccess (OFDMA) and in the uplink it is Single Carrier Frequency Division Multiple Access(SC-FDMA). The Physical Layer performs the functions of link adaptation, power controland cell search for synchronization with other cells and handover.

MAC layer lies above the physical layer and it functions by mapping logical channelscoming from the RLC layer to transport channels and vice versa. The protocol data unit(PDU) that goes down to the physical layer from the MAC layer is called the MAC PDU.The main functions of the MAC layer are scheduling of users, correction of errors throughHybrid Automatic Repeat Request (HARQ) and priority handling among di�erent UEsand di�erent logical channels of the same UE.

The next layer is the Radio Link Control layer (RLC). This layer has three modes ofoperation such as Transparent Mode (TM), Unacknowledged Mode (UM) and Acknowl-edged Mode (AM). TM is used in the initial connection for RLC messages in control planesignaling without the addition of the RLC header. Unacknowledged and acknowledgedmodes use the RLC header to denote whether ARQ is enabled or not. Error correctionthrough ARQ is applicable at the RLC layer and HARQ is applicable at the MAC layer.Other functions of RLC include concatenation, segmentation and reassembly of RLC Ser-vice Data Units (SDUs) for UM and AM transfer.

Packet Data Control Protocol is the next layer and its responsibilities lie in IP dataheader compression, maintenance of sequence numbers, delivering upper layer PDUs inorder, removing duplicates, encryption and decryption of user plane data.

HeNBs do not have any layers above the PDCP layer in the user plane. It commu-nicates with the serving gateway through a di�erent interface called S1-U and there are adi�erent set of layers for this purpose, GPRS Tunneling protocol (GTP-U), User DatagramProtocol (UDP) and layer 2 and 1 protocols that depend on the link being used betweenthe HeNB and the S-GW.

Figure 2.7 illustrates the control plane protocol layers and interfaces that dwell amongthe UE, HeNB and the MME. Between the UE and the HeNB remains the air interface Uuand between the HeNB and the MME is the S1 interface. Radio Resource Control (RRC)and Non Access Stratum (NAS) layers replace the IP and Application layer at the protocolstack of the UE and HeNB interface. Non Access Stratum protocols lie at the top of the


2.5. Requirements for the Functionality of HeNBs

Application

IP

PDCP

RLC

MAC

L1 L1

MAC

PDCP

L1

L2

UDP/IP

GTP-U

IP

GTP-U

UDP/IP

L2

L1

Relay

RLC

L1

L2

UDP/IP

GTP-U

L1

L2

UDP/IP

GTP-U

Relay

Uu S1-U S5/S8a SGi

UE HeNB S-GW P-GW

UDP/IP

L2

Figure 2.6: Protocol Stack- User plane without an HeNB Gateway

stack and this layer is responsible for the management of mobility of the UE. The functionsof the RRC layer include broadcasting of Non Access Stratum and Access Stratum systeminformation, paging and security functions. Between the HeNB and the MME interface thelayers of the protocol stack are L1, L2, IP, Stream Control Transmission Protocol (SCTP)and S1 Application Protocol (S1-AP). L1 and L2 layers depend on the technology of thelink between the HeNB and the MME.

Figure 2.8 demonstrates the two protocol stacks of the control and user planes thatexist between the UE and the HeNB together in the same diagram.

2.5 Requirements for the Functionality of HeNBs

As the HeNBs are di�erent new entities from eNodeBs that serve a di�erent purpose,the technical speci�cation [24] de�nes service requirements for the support of basic func-tions of HeNBs that will enable the mobile operators to provide more advanced services andto improve the user experience. HeNB Installation, identi�cation and location, operationand management, access control, mobility aspects for Home eNodeB, Local IP access andmanaged remote access to home based network are some of the important requirementsamong them.

• HeNB installation, identi�cation and location requirements

These requirements specify some guidelines to follow when installing, provisioning,con�guring or re-con�guring HeNBs. The operator has the authority to con�gure thesettings of a HeNB and set it out of service if it badly a�ects the spectrum usage. In-stalling and activating a new HeNB doesn't require recon�guration at the operator'snetwork and the radio transmitter of a HeNB is activated only after con�gured andauthorized by the operator.



NAS

RRC

PDCP

RLC

MAC

L1 L1

MAC

RRC

L1

L2

IP

S1-AP

NAS

S1-AP

UDP/IP

L2

L1

Relay

RLC

Uu S1-MME SGi

UE HeNB MME

IP

L2

PDCP SCTP SCTP

Figure 2.7: Protocol Stack- Control plane without an HeNB gateway

Physical Layer

Medium Access Control

(MAC)

Radio Link Control

(RLC)

Packet Data Convergence

Protocol (PDCP)

Radio Resource Control

(RRC)

EUTRAN

Related

Protocols

Non Access Stratum

(NAS)Internet Protocol (IP)

Configuration &

Management

Logical Channels

Transport Channels

Physical Channels

L2 & 3

Figure 2.8: EUTRAN protocol stack


2.6. Bene�ts and Challenges for Femtocells

• Operation and management requirements

This speci�es operational and management related issues such as allowing the oper-ator to remotely con�gure the HeNB, deploy software upgrades, detect and reportchanges in RF conditions and perform general operation and management tasks.Moreover, the HeNB supports the automatic discovery of an operator's managementplatform which is used to perform OA&M tasks at the HeNB. Furthermore, the HeNBis allowed to deactivate the air-interface if the connection between the HeNB and theoperator network is lost.

• Access controlThe operator is allowed to con�gure the HeNB as either in open access, closed accessor hybrid access modes. If it's con�gured in open access mode, the HeNB is able toprovide access to any nearby user subject to roaming agreement. This way it per-forms as another base station facilitating handover procedures. But if it's con�guredfor closed access, only users authenticated by the owner are able to get services fromthe HeNB. If it's con�gured for hybrid access, the HeNB can provide services to itsassociated Closed Subscriber Group members and also other nearby users. It's morelike providing services to the closed and open access users. Closed access mode is verycritical for the establishment of this research topic as it's one of the major reasons forthe generation of interference to macro UEs. If a HeNB is con�gured in this mode itbehaves as an interferer to all the UEs that do not belong to its Closed Access Group.The interference analysis in this work is based on the prior assumption that all theHeNBs are con�gured in the CSG mode.

• Local IP access

For the UEs having IP capabilities, local IP access provides access to the internet viaHeNBs. The data tra�c however does not go through the operator's network exceptthrough the operator network devices that are placed inside the place where the HeNBis situated. But the signaling tra�c is designed to go through the operator's network.Using LIPA both the network operator and the user can be bene�ted. Howeverproviding LIPA through HeNBs is a win-win for both the operators and the users.For mobile operators, by providing value added services without investing on extranetwork infrastructure higher revenues can be gained. For users this is a more fasterand secure option as the tra�c within the home network won't travel outside thesubnet. The subscribers can also bene�t from high speed applications such as videostreaming and �le transfers that do not involve the operator core network. Havingto go through the core network could possibly result in bottlenecks and using LIPAthis can be avoided [25]. The Internet Service Providers do not have to be from thesame company of the mobile operator as well.

2.6 Bene�ts and Challenges for Femtocells

The femtocell concept provides advantages for both users and operators. But as anyother newly introduced technology it still has some issues that requires more research. Sec-tions 2.6.1, 2.6.2 and 2.6.3 provide descriptions of advantages and challenges of femtocells.

2.6.1 Advantages for users

• Better indoor coverage: Wall penetration loss is a reason for the weakening of thesignal which arrives from macrocells at indoors. Hence femtocells are a good low cost



option. This is especially advantageous for the cell edge users as they receive furtherweakened signals from the macro cells due to path loss. Furthermore interferencefrom other macro eNodeBs are also high at the cell edge. If a HeNB is deployed insuch a place with a reasonable transmit power a much better indoor coverage can beachieved.

• Lower transmission power at home: Both phone and the base station are now indoors,so they don't need to transmit with higher transmit powers. This is also bene�cialfor the health aspects of the users.

• Increased phone battery life: Since the HeNB receiver is at indoors, the UEs do notneed to transmit at higher powers to achieve a better reception quality. Hence thisincreases phone's battery life.

• Since femtocells are plug and play devices, no technical knowledge is required by theusers for installation and operation.

2.6.2 Advantages for operators

• Higher data rates: The users subscribed to the Mobile Network Operators (MNO)receive higher data rates from femtocells depending on their broadband connectionthrough Local IP Access. The user tra�c goes to the Internet Service Provider insteadto the mobile operator network. Hence the MNO is able to provide better data ratesfor the users while o�oading tra�c from the macrocells.

• Increased Network capacity: Tra�c o�oad from macrocells provides better networkcapacity and it also contributes for a slower growth of the backhaul costs.

• Increased Revenue: MNOs can place special tari�s for calls taken through femtocells.This also depends on the pricing policy of the operator.

2.6.3 Disadvantages of having femtocells

• Interference: This is the main problem of using femtocells as it becomes an interfererto the nearby macro users as well as other femtocell users if it's under co-channeldeployment. More about this will be elaborated in section 2.7 because mitigatingthis interference is the main focus of this thesis

• Quality of service: If the femtocell shares the home backhaul connection for datatra�c with other equipment such as internet browsing and gaming consoles, this mighta�ect the quality of service that it provides to the femto users. For example if someoneuses a video streaming application over the phone, the femtocell might struggle toreach the data rate requirement in a shared connection. Minimum requirements ofthe backhaul capacity must be expressed by the operator when the femto cells arebought. Some QoS di�erentiations as well as link reservation for femto tra�c can beapplied at the subscriber backhaul equipment.

• Spectrum accuracy: Femtocells are low cost devices. It is very di�cult to generatea very accurate spectrum through low cost oscillators inside these devices. Hence3GPP has also relaxed its standards on spectrum accuracy for femtocells from itslater standards starting from Release 8

• Equipment location: Base stations usually �nd there location from the Global Posi-tioning System (GPS). GPS most of the time is unable to �nd locations indoors dueto low signal quality that occurs because of high wall penetration losses.


2.7. The Interference Problem

2.7 The Interference Problem

There are several interference scenarios involving HeNBs, Macro eNBs, MUEs andHUEs. Table 2.2 lists all the possible interference scenarios that are currently identi�edby 3GPP. The scenario that is relevant to this topic is scenario no.2 in the table which isthe interference at the downlink of the MUE from HeNBs.

When an eNodeB is interfering with a UE that is attached to another eNodeB in thedownlink, it's called downlink interference and when a UE is interfering with an eNodeB'sreception from another UE this is called uplink interference. When a HeNB is interferingthe users attached to another HeNB, this type of interference is called downlink co-layerinterference. When an HeNB is interfering the users attached to an eNodeB or vice versa,this is called downlink cross-layer interference. Figures 2.9 and 2.10 depict two scenariosof downlink co-layer and cross-layer interference respectively.

The scenario of downlink cross-layer interference to MUEs discussed in this thesis isa result of several reasons. The �rst reason is that HeNBs are placed inside the coveragearea of eNodeBs. The next reason is that both eNodeBs and HeNBs operate in the samefrequencies which is also called co-channel deployment. Another cause is that, not only theHeNB provides coverage inside a house but there is also a leakage of radiation to the outsidewhich eventually results in interference. This leakage becomes severe if the walls have moreopen spaces or glass windows. Another reason for interference is that the HeNBs are moreoften con�gured in CSGs which was explained in section 2.5 under Access Control. Thismakes handover of a MUE to a HeNB impossible even if it gets the stronger signal fromthe HeNB.

Scenario Aggressor Victim1 UE attached to Home eNodeB Macro eNodeB: Uplink2 Home eNodeB Macro eNodeB: Downlink3 UE attached to Macro eNodeB Home eNodeB: Uplink4 Macro eNodeB Home eNodeB: Downlink5 UE attached to Home eNodeB A Home eNodeB B: Uplink6 Home eNodeB A Home eNodeB B: Down-

link7 UE attached to Home eNodeB

and/or Home eNodeBOther System

8 Other System UE attached to Home eN-odeB and/or Home eN-odeB

Table 2.2: Interference Scenarios [5]

2.8 Intercell Interference Coordination (ICIC)

ICIC is the name used for the methods that are used to control interference in hetero-geneous networks. Interference control is performed in both uplink and downlink. But herethe priority is given to downlink interference control as the focus is on mitigating interfer-ence from HeNB to macro eNodeB user equipment. Interference control in the downlinkcan be basically achieved by two methods, power control and radio resource management.Downlink interference control methods can further be divided as control channel protec-tion and data channel protection methods. The intention of this work is on data channel



High Interference

Home BS

Home BS

Home UE

Home UE

Figure 2.9: Colayer interference

High Interference

HomeUE

Macro BS

Home BS

MacroUE

Figure 2.10: Crosslayer interference

interference control methods.

Before activating any interference mitigating technique a HeNB �rst needs to identifywhether a user is interfered by its transmissions. For that purpose there are several typesof measurements that can be collected. The following section gives some details aboutthose measurement techniques.

2.8.1 HeNB Measurements

There are several measurements gathered by HeNBs which are important for thecontrol of their interference and to maintain coverage. Some measurements are collectedby the UEs that are attached to the HeNBs. Some measurement collections are performedby the downlink receiver of the HeNB. This is also called Network Listen Mode (NLM) ofthe HeNB. Other measurements are collected by the HeNB uplink receiver and this mode ofmeasurement collection is called Radio Environment Measurement(REM) or HeNB sni�er.

Table 2.3 explains a measurement done by HeNBs, Received Interference Power (RIP)when they are being con�gured or during normal operation. This measurement is usefulfor interference mitigation by the HeNB. If the RIP is above a certain predetermined level,this indicates that there's a MUE nearby and the HeNB must lower its power to avoidinterference in the downlink.

Measurement Type Purpose Measurement SourceReceived InterferencePower

Calculation of UL interfer-ence towards HeNB (fromMUE)

HeNB UL Receiver

Table 2.3: Measurements from all cells [6]

Table 2.4 lists two types of measurements done by HeNBs in the downlink whichcan be performed during normal operation or self-con�guration. These two measurementshelp to identify the surrounding cell types such as other HeNBs. Hence the informationcollected by these two measurements are important for mobility handling among HeNBs.


2.8. Intercell Interference Coordination (ICIC)

Measurement Type Purpose Measurement Source

RSRP

Calculation of co-channel DL interferencetowards macro UEs (from HeNB)Calculation of co-channel UL interferencetowards macro layer (from HUEs) HeNB DL ReceiverCalculation of co-channel UL interference HUEtowards HeNB (from MUEs) based on MUE (in case ofestimated MUE Tx powerDetermine hybrid cell)coverage of macro cell (for optimizationof hybrid cell con�guration)

Co-channel Determine quality of macro cell (for HeNB DL ReceiverRSRQ optimization of hybrid cell con�guration) HUE

MUE (in case ofhybrid cell)

Reference Signal Estimation of path loss from HUE toTransmission MeNB HeNB DL ReceiverPower

Physical + Global Allow HeNB to Instruct UEs to HeNB DL ReceiverCell ID measure speci�c cells. HUECo-channel received Measurement is used to determine HeNB DL ReceiverCRS Êc (measured in whether HeNB is close to dominantdBm) Macro cell, or whether it is close to

macro-cell-edge border

Table 2.5: HeNB Measurements from surrounding macro cells [6]

Measurement Type Purpose Measurement SourceCell reselection pri-ority information

Calculation of UL interfer-ence towards HeNB (fromMUE)

HeNB UL Receiver

CSG status and ID Distinction between celllayers based on CSG, andself-construction of neigh-bour list,

HeNB DL Receiver

Table 2.4: HeNB measurements from surrounding cells [6]

Table 2.5 classi�es 5 measurements collected from the surrounding macro cells, Co-channel Reference Signal Received Power (RSRP), Co-channel Reference Signal ReceivedQuality (RSRQ), Reference Signal Transmit Power, Physical and Global Cell Id, Co-channel received CRS Êc. Co-channel RSRP is de�ned as the linear average over thepower contributions (in [W]) of the resource elements that carry cell-speci�c reference sig-nals by 3GPP [26]. Co-channel RSRQ is de�ned by 3GPP as the ratio N×RSRP/(E-UTRAcarrier RSSI), where N is the number of RBs of the E-UTRA carrier RSSI measurementbandwidth [26]. RSSI here means the Received Signal Strength Indicator. Co-channelreceived Cell speci�c Reference Signal Received Power per Resource Element (CRS Êc)is the reference signal received power per resource element present at the HeNB antennaconnector for the reference signal received on the co-channel [6].



Measurement Type Purpose Measurement Source

Co-channel RSRP

Calculation of co-channel DL interferencetowards neighbour HUEs (from HeNB) HeNB DL ReceiverCalculation of co-channel UL interference HUEtowards HeNBs (from HUEs)

Reference Signal Estimation of path loss from HUE to HeNB DL ReceiverTransmission Power HeNB

Allow HeNB to Instruct UEs to measurePhysical + Global speci�c cells HeNB DL ReceiverCell ID Allow UE to report discovered cells to HUE

HeNB

Table 2.6: HeNB measurements from adjacent HeNBs [6]

Table 2.6 lists three types of measurements performed by the HeNB downlink receiver,Co-channel RSRP, Reference signal transmit power, Physical and Global Cell ID. Thesemeasurements are collected from adjacent HeNBs and they can be used for interferencemitigation among them.

2.8.2 Information Exchange

Other than the above mentioned measurements, HeNBs also gather information oninterference control through information exchange with eNodeBs and other HeNBs. Thisoption has the bene�t of obtaining details about uplink and downlink conditions in nearbyeNodeBs and HeNBs when the HeNB con�gures its power and frequency resources. Thereare several ways to perform this information exchange with other eNodeBs.

• Over-the-air information from eNB to HeNB

This scenario involves transfer of vital data among eNodeB and HeNBs directlythrough the air interface. The advantage over direct information exchange is thatit has a low latency. Direct information exchange among eNodeBs and HeNBs canalso be used to coordinate scheduling as well. This helps in reducing interferenceto UEs. But the main disadvantage is that over the air broadcasting can't be usedwhen the eNodeB needs to send di�erent types of data to di�erent HeNBs. The eN-odeB may also not be visible to HeNBs due to fading. This may result in occasionalinterference to the nearby macro users. When the information is read from the air in-terface downlink transmission is also halted which may a�ect the data rate of the user.

• Over-the-air information, (H)eNB to HeNB via UE

In this method information is exchanged among HeNBs through UEs. This also hasthe advantage of low latency and can also be used to reduce interference by sendingscheduling information. This has the added advantage of being able to send di�erenttypes of information to di�erent HeNBs. But for proper operation there should begood links among HeNBs and UEs. The other drawback is Rel. 8 UEs can't be usedto relay these messages.

• X2 based interface between eNB and HeNB, and between HeNBs

The X2 interface that exists among eNodeBs and HeNBs can also be used to trans-fer control information regarding interference management. This method is usedcurrently for the exchange of such information among macro eNodeBs. But for in-



terference control among eNodeBs and HeNBs, this might not be suitable becausethis link is having a high latency. The other reason is that the macro eNodeB has tosend many messages to a larger number of HeNBs in its coverage area unlike in themacro-macro information exchange scenario. But information sent through this linkcan be accurate than information exchanged over the air interface because informa-tion exchanged over the air interface can have more packet drops due to fading. X2being a wired link this problem does not occur. Hence, to reduce the complexity theprocedures over the X2 interface can be limited to only sending Overload Indicator,High Interference Indicator and Relative Narrowband Transmit Power signals whichrequire a higher latency among the eNodeB and HeNBs.

• S1 based interface between eNB and HeNB, and between HeNBs

S1 interface exists between the E-UTRAN and the EPC or in other words betweenthe eNodeBs or HeNBs and the operator core network. This interface can also be usedto exchange messages about interference management among eNodeBs and HeNBs.This also provides a higher accuracy of data than the air interface similar to the X2interface. Di�erent information can be sent to di�erent groups of eNodeBs. But thiscan also increase the load at the MME. Interference mitigation schemes that are usingthis scheme may also face the adverse e�ects of high latency.

2.8.3 Interference Control

This section gives an explanation on the functionality of available interference controlmethods. As explained in section 2.8 the main interference mitigation methods are dividedto power control and resource partition. The resource partition methods are classi�ed intotwo as frequency domain and time domain resource partitioning. There is also a resourcepartitioning method with resource block scheduling in the RBs that have less interference.

2.8.3.1 Power Control Methods

All the available power control methods can be classi�ed into four types as based onHUE measurement, macro eNodeB measurement, HeNB-MUE path loss and GPS basedmaximum output adjustment [6]. A brief description about them is given below.

• HeNB power control based on HUE measurement

HeNB typically con�gures its transmit power based on the measurements taken onthe surrounding RF conditions through Network Listen Mode (NLM) at the downlinkreceiver in order to provide good indoor coverage and to control interference to macrousers as explained in section 2.8.1. But in some situations the measurements taken bythe HeNB might be di�erent from those taken by HUEs or MUEs in the vicinity. Thiscan be due to the di�erence in the indoor environment where the HeNB is situated,as an example the HeNB might be inside another room while the HUE is nearby anouter wall. At this situation the HeNB can't rely only on its own measurements tobe similar to HUE measurements on the channel.

• Power control based on interference measurement from macro eNodeB

In this method the HeNB adjusts its transmit power based on received power of thereference signals from the eNodeB that it receives the strongest signal. Cell Speci�cReference Signal per Resource Element (CRS Êc) which is the reference signal re-ceived power of a resource element is an example for a measurement taken from theair interface. Depending on the strength of the received signal the transmit power of



the HeNB can be controlled in situations such as resource partitioning or setting a�xed power is not enough to control interference and also provide su�cient coverageto HeNB users. The path loss between the HeNB and the MUE is determined by theHeNB depending on the di�erence between the estimated uplink transmit power andthe uplink reception power of the MUE.

• HeNB power control based on HeNB-MUE path loss

Here the HeNB acquires knowledge of the path loss and the wall penetration lossbetween the HeNB and the a�ected MUE and adjusts its transmit power based onthat. The HeNB can also use RSRP as a guide to adjust its transmit power becauseknowing the path loss and wall penetration loss won't be su�cient when it's placedat the edge of a cell. The received signal strength at the MUE is smaller at the cellboundary and it can be high in the middle. Hence the transmit power should beadjusted carefully depending on the location.

The wall penetration loss is estimated using the uplink transmit power of the MUE.The uplink transmit power of the MUE is estimated based on the assumption thatuplink power control is applied for both MUE and HeNB as a UE. This means thatthe HeNB also behaves here similar to a UE that performs uplink power control.When the wall penetration loss is known, it's easier to estimate the path loss usingthe estimated MUE uplink transmit power and the power received at the HeNB.

2.8.3.2 Resource Partitioning

This section gives a brief description of the available resource partitioning techniques inLTE-A that can be used in interference mitigation algorithms. The main two techniquesare called carrier aggregation and almost blank subframe. Additionally an interferencemitigation algorithm can also contain resource block allocation of a HeNB to its usersdepending on the interference levels in their PRBs.

• Frequency domain: Carrier aggregation based ICIC

As explained in section 2.2.1 there are multiple component carriers available in LTE-A. An example scenario is explained in �gure 2.11where the component carriers canbe separated as primary and secondary in a heterogeneous network consisting ofHeNBs and macro eNodeBs. f1 and f2 represent two bandwidths in the frequencyspectrum for the primary and secondary component carriers. In �gure 2.11areas inblack represent control signals, blue represent data and in white areas nothing issent. The macro station will select a separate component carrier as its primary (f1)and will send its control signals in that carrier during a chosen subframe. HeNBspeci�es its own primary component carrier to be f2. Hence for the macro eNodeBthe secondary component carrier will be f2 and for the HeNB this will be f1. TheHeNB does not transmit anything during that subframe in component carrier f1 toavoid any interference and instead use f2 for its transmissions.• Time domain: Almost Blank Subframes

In this approach, if there are HeNBs that are victimized by eNodeBs from severe in-terference, the eNodeB does not transmit any data during certain subframes. Duringthat period the victimized HeNB can transmit with high power so that the UEs getthe maximum exposure to the signal. But the eNodeB may transmit some controlsignals during the muting stage and hence the name Almost Blank Subframe is used.The control signals that are sent during this period are Common reference symbols,



Macrof1

f2

f1

f2

Femto

Control Data

Figure 2.11: An example component carier aggregation scenario

Primary and secondary synchronization signals, Physical broadcast channel (PBCH),System Information Block (SIB)-1 and paging with their associated Physical Down-link Control Channel PDCCH. Figure 2.12 illustrates such a scenario consisting ofAlmost Blank Subframe transmission.

ABSDATA

DATADATA

ABSDATA DATAMacrocell

f1

Femtocell

f1

Control Data

Figure 2.12: An example ABS scenario




3 Scalable and Self-sustained Femtocell

Architecture

T his chapter explains in detail two approaches introduced by this thesis that can beused to mitigate the interference caused by HeNBs on macrocell users. The �rst one

is an analytical approach that adjusts HeNB transmit power based on Channel QualityIndicator (CQI) signals sent by the a�ected macro UEs. Section 3.1 explains how theseCQI signals are used to get information on the channel conditions and achieve e�cientdata transmission by eNodeBs.

The other method is a random PRB selection scheme that the HeNB adopts to trans-mit only on a chosen set of PRBs so that the macro users can bene�t good SINRs in theother PRBs. In this method the HeNB chooses only a subset of random PRBs to allocateto its user and after a predetermined number of TTIs this subset is again randomized.This procedure will be followed by the HeNB during the entire duration the a�ected macrouser is inside the HeNB's interference area.

During the rest of this thesis the �rst interference mitigation method will be termed�HeNB Power Control Scheme� and the other method, �Random PRB Selection Scheme�.Sections 3.2 and 3.3 will exemplify these two approaches in detail.

3.1 CQI Reporting in LTE-A

CQI reports are sent by UEs to eNodeBs through control messages. CQI reportsindicate the required Modulation and Coding Scheme (MCS) from the eNodeB and thesemessages are used by eNodeBs to determine the current channel quality between the UEand itself. The CQI values range from 0 to 15 and higher the and the higher the CQI valueis the higher the MCS that can be used. A better channel quality results in a higher CQI,a higher MCS and hence a higher throughput. Table 3.1 provides the relationship betweenthe CQI value and the MCS.

In this work the Exponential E�ective SINR Mapping (EESM) is used to model theCQI channel reporting. As LTE-A uses OFDMA for the transmission technology in thedownlink, UEs get data in several PRBs in a single transmission. But di�erent PRBs havedi�erent SINRs depending on the available channel condition. When these di�erent SINRvalues are averaged to a single SINR value as explained in section 3.1.1 we get the EESMSINR. This EESM SINR is determined in every TTI when there is a data transmission.Once this value is calculated it is checked against the AWGN curves to determine theappropriate MCS for the chosen set of PRBs. More details on AWGN curves are given insection 4.6

3.1.1 EESM SINR Calculation

This section explains how EESM SINR value is derived from SINR values of theselected PRBs to a particular user. Initially for a correct SINR mapping the followingapproximation must be satis�ed.

BLEP ({γk}) = BLEPAWGN ({γeff}) (3.1)

Here BLEP ({γk}) represents the BLock Error Probability of the state of the channel {γk}and BLEPAWGN ({γeff}) is the Additive White Gaussian Noise (AWGN) BLock Error

3. Scalable and Self-sustained Femtocell Architecture

CQI MCS CQI MCS0 Outage 8 16QAM1 QPSK 9 16QAM2 QPSK 10 64QAM3 QPSK 11 64QAM4 QPSK 12 64QAM5 QPSK 13 64QAM6 QPSK 14 64QAM7 16QAM 15 64QAM

Table 3.1: CQI vs MCS

Probability. Hence it is very important that the following approximation is valid for everyinstantaneous channel realization and not �on average� for a given channel model [27].Therefore a scaling factor β is introduced for each MCS to ful�ll this condition in equation3.3.

The general formula of E�ective SINR is calculated as follows.

SINReff = I−1

(1

N

N∑n=1

I(SINRn)

)(3.2)

where, I(x) is called the information measure function and I−1(x) is the inverse of thatfunction. N denotes the total number of PRBs allocated to a UE and SINRn is the SINRof nth PRB.The de�nition of information measure function of EESM is de�ned as,

I(x) = exp(−xβ

) (3.3)

and its inverse is,I−1(x) = −βln(x) (3.4)

Substituting equation 3.3 and 3.4 in equation 3.2 the e�ective SINR calculation can beperformed as,

SINReff = −βln

[1

N

N∑n=1

exp

(− SINRn

β

)](3.5)

Here β is the MCS dependant scaling factor. Table 3.2 depicts each MCS and its corre-sponding β values.

MCS QPSK QPSK QPSK QPSK QPSKβ 1.4 1.44 1.48 1.5 1.62

MCS 16QAM 16QAM 16QAM 16QAM 16QAMβ 3.10 4.32 5.37 7.71 15.5

MCS 64QAM 64QAM 64QAM 64QAMβ 19.6 24.7 27.6 28

Table 3.2: β values for each MCS [7], [8]


3.2. HeNB Power Control Scheme: The Analytical Approach Based on CQI Signals

3.2 HeNB Power Control Scheme: The Analytical Approach Based on CQISignals

Here the summary of the HeNB Power Control scheme will be given and in the nextsections this will be elaborated further. The main feature of HeNB Power Control schemeis that the HeNB listens to the CQI signals from the macro UEs in its interfering area. Ifthe CQIs messages by a particular user are constantly reporting a lower value, then thiscan be an indication that the HeNB is having an adverse e�ect on this user. Hence theHeNB adjusts its transmit power depending on this CQI value.

As highlighted in section 3.1 CQI values and EESM SINR are related to each other.Therefore the adjustment of the transmit power by the HeNB is only performed to achievea certain drop percentage (x%) of the reported EESM SINR. Section 3.2.2 explains how therelationship of x% and EESM SINR is derived and section 3.2.1 elaborates the assumptionsrequired to assist this derivation.

3.2.1 Assumptions

3.2.1.1 HeNB Position Estimation

The HeNB determines its position during its initialization process. From the prevalentbackhaul link, through ADSL or �ber optic line the HeNB can get information on itsposition from the operator. Precise location information with this regard can be obtainedfrom the operator using the IP address of the HeNB because the operator already knowswhere the location of the HeNB is due to the ADSL or �ber optics subscription of the user.So during instantiation and booting of the HeNB it can send requests to the operatorasking about its location and the operator, using the ADSL information about this user inits registry can give back a relative location for the the location of the ADSL or the �beroptics subscription and therefrom the HeNB location.

The positions and transmit powers of other eNodeBs that the HeNB can interfere withare also received from the operator during this initialization process.

3.2.1.2 Wall Penetration Loss Estimation by the HeNB

HeNB estimates the wall penetration loss based on the received power, Prx,eNB fromthe eNodeB. As the HeNB knows the position of the interfering eNodeB through the initial-ization process information from the Mobile Network Operator, it can calculate the pathloss PLeNB,H between HeNB and the eNodeB. It also knows the transmit power Ptx,eNBof this eNodeB as it receives this information from the operator during the initialization.Hence the wall penetration loss Low can be calculated easily as follows,

Low = Ptx,eNB − Prx,eNB − PLeNB,HeNB. (3.6)

3.2.1.3 Estimation of Path Loss between HeNB and the MUE

HeNB estimates the a�ected UE's path loss using the estimated uplink transmit powerof the MUE and the uplink received power at the HeNB, Prx,MUE according to 3GPPspeci�cations [6]. The estimation of the uplink transmit power of the MUE, Ptx,MUE isbased on the assumption that uplink power control is applied for both MUE and the HeNB.This means that here the HeNB behaves as a UE that uses uplink power control. Herewe can get a relationship between the HeNB uplink transmit power and the MUE uplink



transmit power as follows:

Ptx,MUE = Ptx,HeNB,UL − PLMUE,HeNB − Low (3.7)

But the HeNB measures the interfering MUE's uplink reception power and a relationshipbetween MUE uplink transmit power and HeNB reception power in the uplink can bederived based on the path loss and the wall penetration loss as follows:

Prx,HeNB,UL = Ptx,MUE − PLMUE,HeNB − Low (3.8)

Substituting equation 3.7 in 3.8 a value for the path loss between HeNB and the MUE canbe derived.

PLMUE,HeNB =1

2(Ptx,HeNB,UL − Prx,HeNB,UL)− Low (3.9)

Figure 3.1 further exempli�es the uplink power control process that's required for thecalculation of path loss between the HeNB and the MUE. The bottom half of this �gureshows the positions of the eNodeB, MUE, HeNB and the HUE. The top half explains howthe uplink transmit powers of the MUE and the HeNB behave when those two have uplinkpower control.

3.2.1.4 Detection of an A�ected MUE

HeNB listens to the CQI signals of macro UEs in its vicinity. Because the users aresending these CQI reports in the uplink direction and since the HeNB also belongs to thesame operator it can be con�gured to listen to those. HeNB is only capable of listeningto the uplink transmissions of nearby macro users because signal power tends to decreaseas the users go further away. Hence the HeNB can identify which users are in its vicinity.Moreover a HeNB determines if a UE is a�ected by HeNB interference when the CQI valuestend to drop for a certain duration. If the a�ected UE comes in the direction of the HeNB,then the the UEs CQI value decreases however the Uplink CQI signal strength increases.Increasing received signal strength in the uplink is a clear indication that a UE is nearbyand the distance between this UE and the HeNB is getting reduced.

3.2.1.5 Estimation of Fading and Noise at the MUE

The HeNB is not aware of the amount of fading present at the MUE because fading isa property inherent to the MUE depending on its signal propagation environment. Hencethe HeNB is not capable of acquiring any information regards to this. Therefore in thisparticular interference mitigation scheme it is assumed that the HeNB's estimation ofthe reception power at the MUE is only dependent on the transmit power of HeNB andthe estimated path loss plus wall penetration loss between HeNB and MUE which wasexplained in section 3.2.1.3. This assumption is also true for eNodeB received powerestimation at the macro UE. Since the HeNB knows only the transmit power of the eNodeBand the path loss between eNodeB and the MUE, it is assumed that received power fromeNodeB is only dependent on path loss and eNodeB transmit power.

It is also assumed that thermal noise and the noise �oor of the MUEs are known bythe HeNB. These parameters are also required for the HeNB Power Control algorithm toproperly function.



Low

Rx Power[dBm]

MUE

HeNB

HUE

eNodeB

UL Rx power of eNodeB from MUE

UL Rx power of eNodeB from HeNB

Distance from MUE

Ptx_HeNB_UL

Prx_HeNB_UL

Ptx_MUE

Low

Figure 3.1: Estimation of MUE path loss



3.2.2 Interference Mitigation Methodology

The main intention of this interference mitigation scheme is to achieve a controlledinterference at a MUE depending on the CQI or the EESM SINR values reported by thisuser equipment. This reported SINR includes the interference from the HeNB as well.Using this received SINR the HeNB estimates the SINR without its interference at theMUE. Then the HeNB adjusts its transmit power so that the SINR with its interferenceremains at a certain percentage of the SINR without its interference. By setting thispercentage at a higher level the HeNB is able to keep its interference at the MUE to aminimum. The rest of this section explains how this is achieved in the thesis.

EESM SINR reported by a MUE depends on three main factors: received signal powerfrom the connected eNodeB, received interference power from other eNodeBs and noise.The relationship among these factors and EESM SINR can be approximated as follows:

EESM SINR ≈Prx,eNBI +N

(3.10)

where Prx,eNB is the received power from the connected eNodeB, I is the interference fromother eNodeBs and N is noise. This interference I contains interference from the HeNBand also other surrounding eNodeBs. Hence this equation can be rewritten in the followingway:

EESM SINR = SINRWI ≈Prx.eNB

IeNB,N + Prx,HeNB(3.11)

Here SINRWI is EESM SINR or SINR with HeNB interference, IeNB,N is surroundingeNodeB interference plus noise and Prx,HeNB is the received power from the HeNB. If theinterference from HeNB is excluded from this formula we get,

SINRWOI =Prx,eNBIeNB,N

(3.12)

and SINRWOI denotes the SINR without HeNB interference at the MUE.In this thesis work a relationship between SINR without HeNB interference,

SINRWOI and SINR with HeNB interference SINRWI is formulated using a sensitivityfactor x. Hence this relationship can be stated as follows:

SINRWI = {SINRWOI}x (3.13)

, where 0 < x < 1 and SINRWOI > SINRWI , ∀ SINRWI > 1. Rewriting this in dBscale we get,

SINRWI [dB] = (x)× SINRWOI [dB] (3.14)

,where SINRWOI [dB] > SINRWI [dB] , ∀ SINRWI [dB] > 0.Using the relationship in equation 3.14 the HeNB is capable of estimating the SINR withoutthe interference of itself at the MUE that it receives the CQI report or the EESM SINRin this interference mitigation scheme. Hence the HeNB can adjust its transmit power toachieve an SINR at the MUE that is x times the estimated SINR without its interference.The following part explains how the HeNB transmit power adjustment occurs dependingon the received EESM SINR.

Substituting values in equation 3.11 and 3.12 in equation 3.13 the following relationfor the HeNB received power at the MUE, Prx,HeNB can be achieved,

Prx,HeNB = Prx,eNB ×(1− SINR(1− 1

x)

WI

SINRWI

)(3.15)



As highlighted in section 3.2.1.5 estimated HeNB received power at the MUE is onlydependent on HeNB transmit power Ptx,HeNB, estimated path loss PLMUE,HeNB andestimated wall penetration loss Low. This relation can be given as follows:

Prx,HeNB =Ptx,HeNB

PLMUE,HeNB × Low. (3.16)

Likewise the estimated eNodeB reception power at the MUE is,

Prx,eNB =Ptx,eNB

PLMUE,eNB(3.17)

, where Ptx,eNB is the eNodeB transmit power and PLMUE,eNB is the path loss betweeneNodeB and the MUE. By substituting values of Prx,HeNB and Prx,eNB in equation 3.15 arelationship between HeNB transmit power, EESM SINR and the sensitivity factor x canbe derived which can be presented as follows:

Ptx,HeNB = PLMUE,HeNB × Low ×Ptx,eNB

PLMUE,eNB×

(1− SINR(1− 1

x)

WI

)SINRWI

(3.18)

Rewriting the formula in dB scale,

Ptx,HeNB[dB] = PLMUE,HeNB[dB] + Low[dB] + Ptx,eNB[dB]− PLMUE,eNB[dB]

+(

1− SINR(1− 1x)

WI

)[dB]− SINRWI [dB] (3.19)

When the EESM SINR reported by the MUE, SINRWI [dB] is < 0, to satisfy thecondition SINRWOI [dB] > SINRWI [dB], ∀ SINRWI [dB] < 0, the relationship withSINR without interference, SINRWOI [dB] and sensitivity factor, x changes as follows,

(x)× SINRWI [dB] = SINRWOI [dB] (3.20)

Now the transmit power of the HeNB, Ptx,HeNB changes to,

Ptx,HeNB[dB] = PLMU,HeNB[dB] + Low[dB] + Ptx,eNB[dB]− PLMUE,eNB[dB]

+(

1− SINR(1−x)WI

)[dB]− SINRWI [dB]. (3.21)

Hence the �nal expression for HeNB transmit power, Ptx,HeNB considering equations 3.19and 3.21 can be written as follows:

Ptx,HeNB[dB] = PLMU,HeNB[dB] + Low[dB] + Ptx,eNB[dB]− PLMUE,eNB[dB]

+ f(SINRWI , x)− SINRWI [dB] (3.22)

, where

f(SINRWI ,x) =

{1− SINR(1− 1

x)

WI [dB] if SINRWI [dB] > 0

(1− SINR(1−x)WI [dB] if SINRWI [dB] < 0

When SINRWI [dB] = 0 the interference mitigation scheme continues using the sametransmit power that it was using before. The derivation of transmit power of the HeNBdepending on the EESM SINR, sensitivity factor x and other estimated values such aspath loss and wall penetration loss is the main outcome of this algorithm. Once a MUEreports an EESM SINR value the HeNB uses this formula to adjust its transmit power. Itmust also be highlighted that this determined transmit power is used in PRB basis. Thatmeans once a transmit power is calculated this applies to all the PRBs that are scheduledfor transmission.



3.3 Random PRB Allocation Scheme

LTE-A uses OFDMA as its downlink transmission technology. In OFDMA, the down-link resource allocation is characterized based on the fact that each scheduled UE uses anumber of Physical Resource Blocks (PRBs) while each resource block is assigned only toone UE at a time. In assigning PRBs to users, usually the best set of PRBs that have thehighest SINR are allocated to achieve a higher MCS and ultimately a higher data rate.But for HeNB users, almost all the PRBs have a good SINR such that the users can bescheduled with a high MCS, compared to MUEs. One reason is that HeNB users receive avery good signal quality from HeNBs because these users are not far away from the HeNBand wall penetration loss is also not present. The other advantage the HeNB has is itserves a fewer number of users compared to the eNodeB. Hence the HeNB can a�ord toselect a subset of its PRBs to schedule its users and prevent interference to the surroundingmacro UEs.

The main idea of this interference mitigation scheme is to choose a subset from theset of all PRBs for the HeNB user when a macro user is in the HeNB's coverage area.The PRBs in this subset are chosen randomly. The usage of the chosen PRBs are kept forseveral TTIs and then released for a di�erent set which are again chosen randomly. Thisscheme does not require the HeNB to have a complex solution to identify when a useris nearby. The main idea behind this scheme is to have a simple solution that does notrequire any prior knowledge, assumptions or any complexity.

The main concern of using random PRBs is deciding on how many TTIs the selectedset of PRBs must be used without reshu�ing them and how many PRBs must be chosenrandomly for this subset. In addition to that, this scheme does not guarantee that thechosen subset will not interfere with the macro users, since the subsets are chosen randomlyso there is still a chance that it might be the same ones the user in the vicinity is using.Figure 3.2 explains the Random PRB Selection Scheme in a block diagram.

3.4 Conclusions

This chapter focused on the two interference mitigation schemes that were introducedby this thesis which are unique, simple and novel solutions compared to the state of theart in this area.

The �rst method is an analytical method, HeNB Power Control Scheme and it relieson the CQI or the EESM SINR values of the macro users. This method estimates theSINR without HeNB's interference at the macro UE based on the EESM SINR it receivesand adjusts its transmit power so that EESM SINR is only a certain percentage of SINRwithout its interference. Hence the HeNB has full control of interference that it is goingto create at the macro user. The other advantage is that this scheme does not depend onbackhaul information after the initialization process which is delay prone. As it does notdepend on any delay prone communications and does not rely complex algorithms, thisscheme is able to function without substantial delays. Finally it must be mentioned thatthe assumptions that are made for this scheme are reasonable and they closely follow the3GPP speci�cations.

The other method is the Random PRB Selection scheme which chooses a subset ofPRBs in order to minimize interference at the macro UEs. This method has the advantagesof simplicity, it does not rely on other information such as feedbacks from UEs or eNodeBs,doesn't use the backhaul connection which can have high latency for communications andit also doesn't rely on so many assumptions. The intention here was to develop a dumbinterference mitigation scheme that relies on randomness to deliver e�cient interference


3.4. Conclusions

cancellation.

Select a number of TTIs (num_TTI) to

choose a set of PRBs

Select a new subset of PRBs randonly

Time duration > num_TTI

yes

Select the size for the subset of PRBs

Start

Figure 3.2: Random PRB Selection Scheme in a bloack diagram




4 Channel and Mobility Models

T he signal propagation environment will be �rst examined in this chapter before ex-plaining the channel model which is implemented in the thesis. Later the mobility

model of the users will be explained followed by the link to system level mapping at thesimulator. As there are two types of UEs which are served by the HeNBs and eNodeBs andconsequently having di�erent mobility models, the channel a�ects them di�erently. Hence,those e�ects will be explained here separately with respect to HeNBs and eNodeBs.

4.1 Signal Propagation

The signals that carry information in the mobile wireless propagation environmentare electromagnetic waves. Once these waves are transmitted, they are subjected to manychanges before arriving at the receiver. They go through phases such as attenuation, noiseaddition and fading.

Signal attenuation is the reduction of the power or the path loss of an electromagneticwave which depends on the distance it travels, the medium and the wavelength. Noise isalso added to the signal along the way due to external interferences such as atmosphericsignals, man made noise from similar frequencies and imperfections inherent in the usedequipment.

Fading is a result of the objects that exist in between the transmitter and the receiverand also the mobility of the user. The radio wave that leaves the transmitter is subjectedto re�ection, refraction, di�raction, scattering and absorption with the collision of inter-mediate objects eventually resulting in several signals of di�erent amplitudes arriving fromdi�erent angles at the receiver. The superposition of these signals depending on their am-plitude and phase create constructive and destructive interference which is interpreted asfading in wireless communication theory.

Doppler e�ect is another cause for the fading that is present in a signal. This is promi-nent when a relative motion between the transmitter and the receiver is available. Dopplere�ect creates a frequency shift in each frequency component of the signal depending on therelative speed and its angle of arrival. The change in the frequency of the received signalis called the Doppler shift. But signals from di�erent paths that correspond to di�erentpath lengths may arrive at the receiver. Those signals have di�erent speeds due to varyingpath lengths and the di�erence of the Doppler shifts of each of these components result ina Doppler spread [28].

Channel fading can be classi�ed into two main categories such as Large-scale fadingand Small-scale fading depending on the amplitude variation of the received signal [29].Large-scale fading, also called Shadow Fading or Slow Fading in di�erent texts is a resultof motion in a large area. The attenuation here is a result of large objects such as treesand buildings that span a large area along the path of the receiving signal. The variationof the mean signal level is an indication of a strong presence of Large-scale fading. Thiswill be referred to as Slow fading from here on in this thesis.

Changes in the signal amplitude in a short space of time because of a movement of fewwavelengths is called Small-scale fading. It's a direct result of both relative motion andchanges in the signal environment. If the Doppler spread of the received signal which su�ersfrom Small-scale fading is more than the signal bandwidth it's supposed to be having fastfading. The modeling of slow fading and fast fading in the thesis is explained in sections4.3 & 4.4 respectively.

4. Channel and Mobility Models

Figure 4.1: Multipath, Shadowing and Path Loss Against Distance [3]

As the signals in the real propagation environment the undergo above mentionedchanges until it arrives at the receiver, it's important that these e�ects are modeled properlyin a simulation environment. Hence the following sections give a detailed explanation onthe channel model that's implemented in this thesis.

4.2 Path Loss Models

There are several models that are currently available which illustrate the power atten-uation of a signal. Free space path loss model is one such example for an analytical modelfor path loss. But this can't be used alone in simulations as it models only the power de-cay of a signal with the distance. In practice several empirical models are popular becausethey incorporate measurements taken in various real environments. Okumura model, Hatamodel, COST 231 Extension to Hata model, COST 231-Wal�sh-Ikegami model and Ercegmodel are some examples to the empirical models that are accessible in literature. Butthe path loss models that are being used in this thesis are based on the log distance pathloss model speci�ed by 3GPP [30]. Depending on the positions of the eNodeBs and theHeNBs there are altogether four path loss models deployed here in the thesis, all of whichare speci�ed by [30].

PL1[dB] = 15.3 + 37.6log10R (4.1)

PL2[dB] = 15.3 + 37.6log10R+ Low (4.2)

PL3[dB] = 38.46 + 20log10R+ 0.7d2D,indoor + 18.3n(n+2)/(n+1)−.46 (4.3)

PL4[dB] =max(15.3 + 37.6log10R, 38.46 + 20log10R) + 0.7d2D,indoor (4.4)

+ 18.3n(n+2)/(n+1)−.46 + Low


4.3. Slow Fading Model

R is the distance between the UE and the eNodeB in all the models and it's measuredin meters. Equation 4.1 is the model used for path loss between an eNodeB and UEsplaced outside houses. Low is the wall penetration loss and the value used for that is 20dBin simulations. Eq. 4.2 is the model for path loss between an eNodeB and a UE that'sinside a house. Eq. 4.3 is for a UE inside a house served by an HeNB placed in the samehouse and the �nal model is for a UE outside a house but receiving signals from an HeNB.d2D,indoor is measured in meters and 0.7dB/m is the the loss due to internal walls modeledas a log-linear value. n is the number of penetrated �oors inside a house.

Because internal walls and multi-�oored buildings are not modeled in the thesis, equa-tions 4.3 and 4.4 can be reduced as follows.

PL3[dB] = 38.46 + 20log10R (4.5)

PL4[dB] = max(15.3 + 37.6log10R, 38.46 + 20log10R) + Low (4.6)

Figure 4.2 is an example for a path loss map generated for a 100m × 100m area for thepath loss map equation 4.5. The HeNB is assumed to be placed at the (50, 50) point andthe distance is measured in meters. For the simulations two dimensional arrays of pathloss maps for a 100m × 100m area are created for HeNBs with a resolution of 1m. It'sassumed that the interference from HeNBs won't a�ect substantially beyond 100m.

For eNodeBs a path loss map is used for a 2400m x 2080m area and it's converted toa two dimensional array having a resolution of 5m between two points. These path lossmaps were created for a 7 cell structure having an inter eNodeB distance of 500m by theopen source Vienna Simulator [31].

4.3 Slow Fading Model

As explained in section 4.1 slow fading is a random behavior. It depends on thenature of the environment that the signal travels. Hence an approach based on probabilityis required instead of a deterministic model in this situation. The probability densityfunction of a signal having Slow fading closely follows the Log-Normal distribution withzero mean and constant variance. But the correlation in time or space are also factors indetermining a proper model for slow fading of eNodeB and HeNB UEs. In this sectiononly the method of deriving a slow fading map is discussed, whereas for an eNodeB it isalready implemented in the simulator.

In [32] a model was proposed for slow fading, a Log-Normal distribution with timecorrelation. This was extended in [33] for spatial correlation instead of time. Having a spa-tially correlated map is better for a simulation because the slow fading value for each pointis calculated prior to the simulation which results in reducing the simulation complexity.For this work it requires at least a 100m x 100m slow fading map with each point having1m distant from each other for a HeNB and for eNodeBs a slow fading map of 2400m x2080m with a distance of 5m between two values is required. The 3GPP speci�cation forHeNB simulation parameters [30] require the mean of slow fading samples of eNodeBs tobe with zero mean and 8dB standard deviation and for HeNBs they should have 0 meanand 4dB standard deviation with correaltion distances as 50m and 3m respectively.

In the following sections the derivation of a slow fading map for an HeNB is discussed.The slow fading map derivation method for an eNodeB is exactly the same to that of aHeNB as given in the open source Vienna simulator [31]. Instead of calculating the valuesthe map is obtained from a simulation run for an eNodeB. But for a HeNB, obtaining the



Figure 4.2: Path Loss Map for a 100m × 100m Area

map from the Vienna simulator is not possible because the correlation distance is di�erentfor HeNBs.

The conventional way of creating a slow fading map with spatial correlation is to �rstgenerate the uncorrelated slow fading matrix a with a Log-Normal distribution [34]. Thismatrix is then multiplied by the Cholesky factor L of the correlation matrix R of matrix awhich results in a correlated log normally distributed matrix s. e.g. Choose a such that,

E{aaT } = I (4.7)

According to [33] the correlation function between two points of the map is,

r(x) = e−αx (4.8)

where α is the inverse of the correlation distance and x is the distance between two neigh-boring points in the map that the fading values are calculated. Then for all the points inthe map, a correlation matrix R can be derived.

R = {LLT } = E{ssT } (4.9)

Hence the matrix s can be obtained by the multiplication of the Cholesky factor of R withthe uncorrelated slow fading matrix a,

s = La (4.10)

But this becomes computationally and memory wise expensive if the matrix a is alarge one. Hence [34] introduced a method that overcomes this barrier. Using this method


4.3. Slow Fading Model

the computational complexity can be drastically reduced if the fading values are derivedbased only on the neighboring correlated fading values in the map.

As an example, for three slow fading values as illustrated in �gure 4.3 each correlatedslow fading value s1, s2, s3 can be calculated using the expressions 4.8 & 4.10 as follows:

s1 = a1 (4.11)

Since s1 is the beginning point of this algorithm it only depends on the uncorrelated fadingvalue a1.

s2 = r(x)s1 +√

1− r2(x) a2 (4.12)

s3 = r(x)s2 + r(x)√

1− r2(x) a3 (4.13)

To calculate s2 and s3 correlation matrix R and it's Cholesky factor matrix L are used,

R =

(1 r(x)

r(x) 1

)& L =

(1 0

r(x)√

1− r2(x)

)(4.14)

S1 S2 S3

r(x) r(x)

r(2x)

Figure 4.3: A Simpli�ed Example of Generating Correlated Slow Fading Values

This idea can be extended to e�ciently generate a two dimensional map of spatiallycorrelated shadow fading values by taking only the neighboring values into account for thecorrelation operation as observed in [34]. In this method a correlation matrix of 5 × 5values can be considered at a time to get the correlated slow fading value of the 5th point.Figure 4.4 shows a pattern of four points that is used to derive the 5th correlated slowfading point.The correlation matrix R5 for 5 points is used to derive the Cholesky factor L5, which isalso a 5× 5 matrix.

R5 =

1 r(δ) r(2δ) r(δ) r(

√2δ)

r(δ) 1 r(δ) r(√

2δ) r(δ)

r(2δ) r(δ) 1 r(√

5δ) r(√

2δ)

r(δ) r(√

2δ) r(√

5δ) 1 r(δ)

r(√

2δ) r(δ) r(√

2δ) r(δ) 1

As the �rst four values of the vector s is known already, instead of the matrix multiplications = La, s5 can be derived straightaway using the multiplication of the last row of matrixL with the vector a as follows.

s5 = Llastrow

a1a2a3a4a5



1 2 3 4 5

m+1 m+2 m+3 m+4

2m+1 2m+2 2m+3

. . . m-1 m

2m+4

m+5 . . . 2m-1 2m

. . .

.

.

.

Figure 4.4: Generating a correlated 2D slow fading map using 5 neighboring points

This way several iterations have to be done to derive the correlated slow fading values forall the points in the �gure 4.4. Figure 4.5 is an example result for a 100m×100m spatiallycorrelated slow fading map derived through this method. This map is then converted toa two dimensional array with each point representing the fading and the resolution of twopoints is 1m.

Figure 4.5: A 100m × 100m Correlated Slow Fading Map for a HeNB with mean 0 andstd. dev. 4dB


4.4. Fast Fading Model

Tap Channel A Doppler SpectrumRelative Delay Average Power

(ns) (dB)1 0 0 �at2 50 -3.0 �at3 110 -10.0 �at4 170 -18.0 �at5 290 -26.0 �at6 310 -32.0 �at

Table 4.1: ITU Channel Model for PedB

4.4 Fast Fading Model

The fast fading model used in this thesis is a Jakes'-like model. Hence the fast fadingattenuation depends on both time and frequency as it considers delay spread for frequencyselectivity and Doppler spread for frequency selectivity. Similar to the slow fading andpath loss models, here in the thesis the calculation method of the fast fading map for aHeNB UE is explained.

The HUEs travel at a 3kmph speed inside a house which prompts the Doppler spread.The power delay pro�le caused by multipath propagation which is the reason for frequencyselectivity is modeled using the ITU Pedestrian B channel speci�cation [35] which is a verycommonly used medium delay empirical channel model for o�ce environments. Table 4.1gives the speci�ed values for the mulitpath power delay pro�le in the PedB channel model.Figure 4.6 depicts an example Jakes'-like fast fading model which is similar to the one usedfor HeNB UEs in the thesis.

Figure 4.6: Fast Fading Map for a HeNB UE with 3kmph speed having the PedB channelmodel

The MUEs travel at a speed of 120kmph outside the houses and its channel trace ismodeled according to ITU Vehicular channel speci�cation [35], [4] .



As it is evident from �gure 4.6, fast fading attenuation a�ects each users' PRB dif-ferently because of the time and frequency selectivity. Unlike in path loss and slow fadingcalculations fast fading has to be calculated separately for each PRB.

4.5 Signal to Interference and Noise Ratio (SINR)

SINR is the ratio between received signal power to interference and noise power mea-sured at a UE. This is calculated per PRB. Since all the losses are accounted in the previoussections and the transmit power of an eNodeB is known, the SINR per PRB of a UE canbe calculated. As the transmit powers of eNodeBs and HeNBs are di�erent and the wayhow the interferences a�ect the respective UEs are di�erent, the SINR calculation is donefor those two separately in sections 4.5.1 and 4.5.2.

4.5.1 SINR Calculation for a HeNB UE

Eq. 4.15 calculates the SINR of a HeNB UE. SINRr,v is the SINR of the rth resourceblock of the vth user equipment. Ptx,F is the transmit power of the femtocell for thatPRB. NF is the noise �oor created by all the unwanted noise sources in the communicationsystem and N0 is the thermal noise.

SINRr,v[dB] = Ptx,F − Lossesr,v −NF −N0 (4.15)

Lossesr,v in the expression 4.16 is the term used to take into account all the losses thatthe signal encounters till it reaches the vth HUE for the rth resource block. As this is aHeNB UE which is placed indoors, the path loss equation 4.3 has to be used. Fast fadingchanges per PRB and FF r,v represents the fast fading of the rth PRB of the vth HUE.Slow fading depends only on the HUE position, hence SF v is used.

Lossesr,v[dB] = PLv3 + FF r,v + SF v + 10 log10(Ir,v)

(4.16)

Ir,v in 4.17 is the interference that the HUE gets from all the eNodeBs which is furtherelaborated in eq. 4.17. Interference from other HeNBs inside other houses is not consideredhere because the signal power reduces drastically when it penetrates two walls, thereforeonly the interference from eNodeBs are collected. The set of interfering eNodeBs andHeNBs are denoted byMint and Fint respectively in equations 4.17 & 4.20. The servingeNodeB or HeNB will not belong to either Mint or Fint. Ptx,M is the transmit powerof an eNodeB per PRB. Path loss equation 4.2 has to be considered here because theuser equipment is inside a building and the interferer is an eNodeB. The term vi is usedto denote the path loss or slow fading at the vth UE that receives interference from ith

eNodeB.

Ir,v =∑

i∈Mint

(PLvi2 × SF

vi)Ptx,M (4.17)

4.5.2 SINR Calculation for a eNodeB UE

The SINR that's observed by the UE u served by an eNodeB for the PRB r in theexpression 4.18 is SINR r,u. Ptx,M is the transmit power of an eNodeB per PRB.

SINR r,u[dB] = Ptx,M − Losses r,u −NF −N0 (4.18)


4.6. Link to System Level Mapping

The losses of that UE, Losses r,u in eq. 4.19 is similar to what's explained in the previoussection. The UE receives power from an eNodeB and hence the path loss eq. 4.1 is used.

Losses r,u[dB] = PLu1 + FF r,u + SF u + 10 log10(I r,u

)(4.19)

The interference in eq. 4.20, I r,u depends on all the interferences from eNodeBs andHeNBs in the vicinity. Interference from all HeNBs are counted only if the UE falls withinthe 100m × 100m coverage area of a HeNB. Eq. 4.1 is used for UEs which are interferedby eNodeBs. For UEs interfered by HeNBs eq. 4.4 must be used. The terms ui & ukare used to denote the interferences from ith & kth eNodeB and HeNB respectively by theuser equipment u. The term Fk is used in Ptx,Fk

because the transmit powers of di�erentHeNBs can vary as they use power control to reduce interference to user equipment servedby eNodeBs. Equation 4.20 is given here in linear scale and hence path loss and slow fadingterms should multiply with transmit power to get the interference term of each eNodeB.After that these all these interference terms are added up to get the total interference fromall the eNodeBs and HeNBs.

I r,u =∑

i∈Mint

(PLui1 × SF

ui)Ptx,M +

∑k∈Fint

(PLuk4 × SF

uk)Ptx,Fk

(4.20)

4.6 Link to System Level Mapping

Wireless network simulator is used as a tool to predict the performance of cellularnetworks. The type of of simulators that are used for this can be classi�ed into two:system level simulators and link level simulators. Link level simulators model the physicallink between the UE and the eNodeB that include modulation, channel coding equalizationand MIMO [4]. System level simulators are used to model the whole network which alsoincludes the link between the eNodeB and the UE. Hence the system level simulators involvea huge complexity. This complexity can be reduced by mapping techniques between thesystem and link level which is known as link to system level mapping. As this thesis relieson a system level simulator, a link to system level mapping method is required to get thecorrect link level characteristics at the system level simulation.

In link to system level mapping, the SINR of each used PRB needs to be mapped toan average SINR. In the downlink this is done according to the Exponential E�ective SINRMapping method [36]. The obtained average SINR is �rst compared with the target SINRof the highest Modulation Coding Scheme (MCS). If this SINR can achieve a Block ErrorRate(BLER) less than 10% for the chosen MCS as given in �gure 4.7, then this MCS ischosen. If the BLER is higher, then the next lower MCS is chosen and compared againstthe BLER vs SINR curve until a suitable MCS is chosen. Once the MCS is obtained,the Transport Block Size (TBS) for the set of chosen PRBs can be determined. For datatransmission choosing a higher MCS is always important as it increases the data rate. Butfor that to materialize a good channel is important.

4.7 The Mobility Model

The HeNB UEs and macro UEs have two di�erent mobility models. The macro UEstravel only inside the macrocell area that it is connected to. The macro users travel atdi�erent speeds depending on the chosen simulation scenario either at pedestrian speeds orvehicular speeds, but the home users only travel at 3 km/h which is the speci�ed pedestrianspeed. When a macro user comes towards the edge of the cell, it changes its direction to



Figure 4.7: AWGN Channel BLER vs. SINR Curve [4]

a random direction inside that cell. Macro users do not come inside a house and they alsodo not change their direction once they encounter a wall of a house on their way. Thisis done to avoid the extreme interference they encounter inside houses. This implies thatwhen a macro UE from outside enters a house, it belongs to the Closed Subscriber Groupof that house and hence the HeNB doesn't behave as an interference source.

HeNB users on the other hand only travel inside a 15m × 15m house. When thereis a wall on its way, they choose a random direction inside that house. A HeNB canaccompany several HeNB users inside a house and they always stays inside that house.But the eNodeBs do not serve any of the HUEs placed in their respective coverage areas.

Figure 4.8 illustrates the mobility of a HeNB and a macro user having the abovementioned behavior. In �gure 4.8 the red line marks the eNodeB coverage area, 100m ×100m yellow rectangle represents the HeNB interference area and the light blue rectanglerepresents the HeNB coverage area. The di�erence of the HeNB coverage area and theinterference area is that the HeNB doesn't serve any users beyond the blue area althoughthe macro UEs can receive its power as interference. Hence the path loss and slow fadingmaps that were created for the HeNB as explained in previous sections span this entireyellow area.


4.7. The Mobility Model

Figure 4.8: Mobility Model




5 Simulation Environment

T his chapter explains the simulation environment of the ComNets LTE-A System LevelSimulator [4], [19], [20] and [21] in the OPNET modeler 17.5 software. First a brief

introduction of the simulation structure is given. Then the Node and Process models of theimportant objects are explained. Finally the simulation parameters and the justi�cationfor using them is presented.

5.1 Simulator Overview

As mentioned earlier, the LTE-A simulation model used in the thesis work is developedin OPNET software environment. OPNET Modeler is a hierarchical modeling environmentwhich is based on C/C++ as the programming tool. It also has an advanced GraphicalUser Interface that is can be used for debugging and result analysis. Some of key elementsof the OPNET Modeler are a model library where many protocols and vendor speci�cnode implementations, Object oriented Programming (OOP) and also a 32-bit and 64-bit parallel and serial simulation kernel. OPNET Modeler is a constitution of severalhierarchical editors such as project editors, node editors, process editors and source codeeditors as shown in �gure 5.1.

Figure 5.2 illustrates the environment that is used for simulations. There are mod-ules for Application, Application Pro�le, Global UE List, Remote Server, aGW, Routers,eNodeBs, HeNBs and UEs. The module Application is used to de�ne and con�gure applica-tions of the UEs. As examples there are applications for Voice over IP (VoIP), Email, FTP,HTTP, video conferencing, Remote Login, peer to peer �le sharing, print and database ac-cess. The module Pro�le de�nes and con�gures tra�c models such as simulation operationmodes, start time, simulation duration and repeatability for di�erent applications. RemoteServer is the remote application server and aGW is used to route and forward data packetsbetween the remote server and the radio access network. R1, R2, R3 and R4 are IP basedrouters in the transport network. Global UE List gathers users' and eNodeB's information,collects SNR of each user and manages the mobility of each user in each TTI. UEs are themobile users in the network. There are 7 eNodeBs in a 7 cell structure and HeNBs areonly inside the center cell.

5.2 The Node Model

The hierarchy of an OPNET module is separated into three stages such as the LogicalNetwork where the attributes are set for individual devices, Node Model representingthe protocol stack and Process Model for actual functionality of each device. Figure 5.3illustrates the node model of both eNodeBs and HeNBs. The node model is similar forboth since the implemented functionality is similar in them. HeNB node model would bedi�erent at the EPC interface if a HeNB gateway or local IP access was implemented.

5.3 The Process Model

In each layer of the node model, there exists a process model. Except for Physical,MAC, PDCP and RLC layers, standard Opnet models are used for process models. Theprocess models are represented by Finite State Machines (FSMs). Figure 5.4 represents

5. Simulation Environment

Project Editor

Node Editor

Process Editor

Code Editor

Figure 5.1: OPNET Modeler environment


5.3. The Process Model

Figure 5.2: Simulation Scenario

the eNodeB and HeNB process model of the MAC layer and �gure 5.5 refers to the processmodel of Global_UE_List.

In �gure 5.4 red and green bubbles represent the unforced and forced states respec-tively and arrows are used to represent transitions from each state. Forced states exitwithout any additional interrupts whereas unforced states always wait for an external in-terrupt to exit to another state. State transitions are triggered by interrupts and once astate gets the execution time all its C or C++ codes in the enter executives are executed.Enter executives represent the C or C++ codes in the top half of a red or green bubble.Before exiting that state all the exit executives are also implemented and exit executivesrepresent the C or C++ codes in the bottom half of a red or green bubble.

The work of this thesis is done at the process model of Global_UE_List and at theprocess model of the MAC layer of eNodeBs and HeNBs. At the Global_UE_List, thechannel model and the mobility model for both the HeNB and eNodeB UEs are imple-mented as explained in Chapter 4. In each TTI the scheduler at the MAC layer of theeNodeBs and HeNBs schedule the UEs on PRBs having higher SINR values measured inthe previous TTI. The Mobility state at the Global_UE_List updates the user positionsfor the current TTI. Then the control goes back to the MAC layer of both eNodeBs andHeNBs where transmission of data and HARQ takes place. The SINR at each PRB is alsomeasured at this instant which will be used for scheduling in the next TTI.



Figure 5.3: eNodeB and HeNB Node Model

Figure 5.4: eNodeB and HeNB MAC Layer Process Model


5.3. The Process Model

Figure 5.5: Global UE List Process Model




6 Simulation Results and Analysis

So far in this work two novel HeNB interference mitigation schemes were developed,HeNB architecture was analyzed and a model for HeNBs was implemented in the

ComNets LTE-A system level simulator [4], [19], [20] and [21] in OPNET Modeler. Thechannel models for HeNB users with path loss, slow fading and fast fading were also imple-mented in the simulator. The �nal task of this work is to simulate a real world situationwhere the HeNBs are interfering the mobile macro users to evaluate the performance ofthe two interference mitigation schemes.

The main aim of this chapter is to analyze and compare the results of the two in-terference mitigation schemes, HeNB Power Control Scheme and Random PRB SelectionScheme. The performance of the two schemes are compared here in terms of the physi-cal aspects such as SINR and also with regards to the performance of users' applicationshaving di�erent Quality of Service (QoS). These comparisons are performed in order todemonstrate the ability of the two schemes to produce desirable results under dynamicinterference conditions.

This chapter explains the types simulation scenarios that are developed in the thesis,types of applications that are used to con�gure users in such scenarios, types of parametersthat are con�gured in user applications and �nally analyzes the results obtained from thesimulations.

6.1 Simulation Parameters

This section illustrates the type of parameters and there values that are con�gured forthe simulations. Simulations are done with a seven cell structure. The center cell consistsof ten macro UEs and the surrounding cells have 5 macro UEs each. Figure 5.2 illustratesa scenario in the simulations which shows how the UEs, eNodeBs and HeNBs are arrangedinside the cells. All the macro users are placed randomly inside their respective cell areas.These macro UEs are con�gured to travel only within their eNB coverage and not outside,since the focus of the analysis is of the e�ect of the HeNB on the macro users and thehandover scenario is not of interest in this analysis.

HeNBs in the simulator are placed inside small indoor apartments and the apartmentsare modeled with an area of 15m× 15m. The walls of the apartments are modeled to havea 20 dB wall penetration loss. HeNBs and there apartments are placed only in the centercell and there are four apartments in this cell. Inside each apartment there is a HeNBand a HUE. Each apartment is 150m away from the center eNodeB and �gure 6.2 showsthe placement of these apartments inside the cell area. All the HeNB users are placed ata random point inside the apartment that they belong to. All HeNBs are con�gured tohave only one home user and hence there are four home UEs altogether in the center cell.However, realistically the number of HeNB users inside an apartment is limited dependingon the the type of households and for the simulations of this work one HeNB user is chosento simplify the scenario.Table 6.1 depicts all the general parameters used in the simulation scenarios.

As mentioned earlier here are in total ten macro users in the center cell. Five of themare con�gured with Voice over IP (VoIP), another three UEs use FTP and another twoare con�gured as Video users to compare the behavior of Guaranteed Bit Rate and NonGuaranteed Bit Rate users under the two interference mitigation schemes.

6. Simulation Results and Analysis

Figure 6.1: Simulation Scenario

Figure 6.2: HenB Positions


6.1. Simulation Parameters

Parameter Value

Downlink operating frequency 2.0 GHzNumber of cells 7Inter eNodeB distance 500mMUEs in the center cell 10MUEs in each surrounding cell 5Apartment size 15 × 15 m2

HeNBs in the center cell 4HUEs per HeNB 1Total number of PRBs 25eNodeB transmit power per PRB -4 dBmHeNB total transmit power (without power control) 0 dBmNoise per PRB -120.447 dBmNoise �oor 9 dBWall penetration loss 20 dBUE speed 3 kmph

Table 6.1: Simulation Parameters

The HeNB users are con�gured as video users having a speed of 18 Mbps. Themotivation for con�guring them with such a data rate is, since there is only one HUEthat is associated with a HeNB, in order to provide a very high interference in all thePRBs for the macro users, the user application must have a very high throughput. Havinginterference in all the PRBs is vital for the result analysis because this will provide a clearpicture of the performance of the interference mitigation schemes under worst conditionsfor the macro UEs. Following sections illustrate further on the con�guration parametersof VoIP, video and FTP applications.

6.1.1 FTP Tra�c Model

Table 6.2 shows the parameters con�gured for FTP users. Parameter `Command Mix'denotes the percentage of FTP download to FTP uploads. Setting this to 100% meansthat the application performs only FTP downloads. Inter-request time here denotes thetime taken for the next �le request once a �le download is completed. Request for the next�le download is sent only after the current download is completed.

The simulator consists of eight types of quality of service classes and each class hasa di�erent QoS characteristic and this means that each has di�erent priority over the airinterface. The types of quality of service classes arranged in the order of lowest priority tohighest are Best E�ort, Background, Standard, Excellent E�ort, Streaming Multimedia,Interactive Multimedia, Interactive Voice and Reserved.

VoIP application users require the highest priority and they are con�gured with Inter-active Multimedia in the simulator. Video streaming users are con�gured with ExcellentE�ort and FTP that requires the lowest priority of the three are con�gured with BestE�ort tra�c in the simulation scenarios.

6.1.2 VoIP Tra�c Model

Table 6.3 lists the parameters used by VoIP users. VoIP application's data rate forthe encoder scheme GSM EFR is 12.2 kbps and it belongs to the Adaptive Multi-Ratecodecs family which is an audio data compression scheme optimized for speech coding.



Parameter Value

Command Mix (Get/Total) 100%Inter-request Time (seconds) 1Type of Service Best E�ortFile Size 1 MB

Table 6.2: FTP Tra�c Model Parameters

The Type of Service (TOS) parameter is con�gured as `EF' which corresponds to Inter-active Multimedia tra�c. The Type of Service of VoIP is chosen to be higher than Video(Excellent E�ort) and FTP (Best E�ort). The parameter `Tra�c Mix' speci�es if thetra�c is generated as pure discrete or pure background or part discrete/part backgroundtra�c.

Parameter Value

Encoder Scheme GSM EFRVoice Frames per Packet 1Type of Service AF33Tra�c mix (%) All discreteConversation environment Land phone - Quiet room

Table 6.3: VoIP Tra�c Model Parameters

6.1.3 Video Tra�c Model

Table 6.4 shows the parameters used by Video users. A Frame inter-arrival time of15 frames/s and a Frame size of 2133 Bytes contribute to a bit rate of 256 kbps. Type ofService of Video is AF31 which corresponds to the quality of service class Excellent E�ort.Tra�c mix parameter is con�gured as All Discrete similar to VoIP users.

Parameter Value

Frame inter-arrival time 15 frames/sFrame size 2133 BytesType of Service EFTra�c mix All discrete

Table 6.4: Video Streaming Model Parameters

6.2 Simulation Scenarios

Simulations are done to compare results of the two interference mitigation schemesintroduced in chapter 3, HeNB Power Control scheme and Random PRB Selection scheme.The performance of the HeNB Power Control scheme is examined using three scenarios95%, 90% and 85%. These percentages re�ect the amount of SINR reduction that is ex-pected at the macro UE due to these three scenarios. The results of these are also comparedwith the results of the other interference mitigation scheme, Random PRB Selection. Tocompare the impact of HeNBs at the macro UEs two reference scenarios are required, ascenario having no interference from HeNBs, `No HeNB' which is the ideal situation and a


6.3. Statistical Evaluation of Simulation Results

Scenario Used term

HeNB Power Control: 95% SINR reduction `95%'HeNB Power Control: 90% SINR reduction `90%'HeNB Power Control: 85% SINR reduction `85%'Random PRB Selection `Random'HeNB with no interference `No HeNB'HeNB with �xed transmit power `Fixed'

Table 6.5: Scenarios types used in the simulations and the terms used for them

scenario having maximum interference from the HeNBs with �xed transmit power, `Fixed'which is the worst possible situation. Hence there are altogether six scenarios to collect re-sults here and they are listed in table together with the terms used for them in simulations6.5.

Random PRB Selection Scheme implemented in the simulations is con�gured to choose5 random PRBs within every 10 TTIs. It must be highlighted that the values for the numberof PRBs and TTIs are chosen randomly here and these are not the optimum values. Amore detailed analysis is required to �ne tune these parameters.

The two interference mitigation schemes are activated at the HeNB when a UE entersthe interfering area. Otherwise normal scheduling with a �xed transmit power is used forthe HeNB users.

The type of results collected from the mentioned six scenarios are as follows. For FTPusers the EESM SINRs and the download response times are compared during the periodswhere there's interference from HeNBs. For VoIP users, the Mean Opinion Scores (MOS),end-to-end delays and EESM SINRs are compared. Finally for Video users the end-to-enddelays and EESM SINRs are compared.

MOS measures the subjective quality of a voice call and returns a scalar one digit scoreto express the status of the call quality [4]. The MOS values range from 1 to 5 with 5 beingthe best quality and 1 the worst quality. MOS values are dependent on the end-to-enddelays and jitter of the delay of VoIP users and this relationship is given in the �gure 6.3.

6.3 Statistical Evaluation of Simulation Results

Results of the simulations performed with several runs and di�erent seeds in thisthesis are presented as mean values together with a con�dence interval. Con�dence intervalmethod is a commonly used statistical method to denote the amount of error introducedby the sample mean from the expected value of a population. Hence a brief explanationon the calculation of the con�dence interval is given here.

Let x1, x2, x3, x4,...xK be an observed set of numbers from a population that's contin-uously distributed with expected value µ, then the mean x̄ of the observed set of samplesof that population can be calculated as:

x̄ =1

K

K∑i=1

xi (6.1)

The variance s2 of those samples are calculated as,

s2 =1

K − 1

K∑i=1

(xi − x̄)2 (6.2)



Figure 6.3: MOS values vs End to end delay of VoIP users [4]


6.4. Results Analysis

If the con�dence level is decided to be 100(1− α)%, then the con�dence interval canbe derived as {x̄−Zα/2. s√

K, x̄+Zα/2.

s√K} where Zα/2 is the upper α/2 critical value of the

standard normal distribution which can be read from a standard distribution table. Whenthe number of samples that are used to determine the sample mean is < 30, Student'st-distribution is used to calculate the con�dence interval. Hence the con�dence intervalcan be determined from: {x̄− tα/2. s√

K, x̄+ tα/2.

s√K} where tα/2 is the upper critical value

of Student's t-distribution and can be read from a Student's t-distribution table. Figure6.4 shows the PDF of a Student's t distribution with con�dence interval and con�dencelevel.

100(1 - α)%

Figure 6.4: PDF of the Student's t distribution with con�dence interval and con�dencelevel

6.4 Results Analysis

Results in this section are obtained after ten simulation runs with ten di�erent seedsfor six di�erent scenarios. Three scenarios have HeNB Power Control scheme enabled with95%, 90% and 85% SINR senitivity factors, one scenario is with HeNBs disabled which isdenoted as `No HeNB' in the results, one scenario is with �xed transmit power and normalscheduling which is referenced in the results as `Fixed' and one scenario is with RandomPRB Selection scheme enabled which is referenced in the results as `Random'. Once theten simulations for the above six scenarios are performed, mean values of the results arecalculated and a 95% con�dence interval is calculated using Student's t-distribution. Thisdistribution is used for con�dence interval calculation because the number of degrees of



freedom are nine here.As illustrated in chapter 4 macro UEs have the liberty to travel inside the entire

cell that it's associated to. Hence they can be inside the HeNB interference area during acertain period and it can be outside this area at other times. All the results in the followingsections are analyzed during the time the macro UEs are inside HeNB interference premisesbecause it's only during that time a better conclusion on performance of the interferencemitigation schemes can be derived.

The rest of this chapter is organized as follows: Sections 6.4.1, 6.4.2 and 6.4.3 analyzethe results of VoIP, FTP and Video users respectively. Section 6.4.4 analyzes the per-formance of HeNB users under the two interference mitigation schemes and section 6.4.5analyzes the performance of HeNB Power Control scheme's performance when the HeNBsare placed near to the eNodeB.

6.4.1 VoIP User Results

Figure 6.5a shows the bar graph of the VoIP users' mean SINR value with 95% con-�dence interval calculated over 10 simulations runs. The macro users of the `No HeNB'scenario have the highest mean EESM SINR as there's no interference from the HeNBsat the macro UEs. The Random PRB selection scheme using 5 PRBs has the next high-est SINR. The performances for the `95%', `90%' and `85%' of the HeNB Power Controlscheme are in the middle range and the `Fixed' transmit power scheme which receives themaximum interference from the HeNB has the poorest performance as expected.

Figure 6.5b shows the relative SINR performance of the two interference mitigationschemes (`95%', `90%', `85%' and `Random') and the `Fixed' transmit power scheme `Fixed'in comparison to the `No HeNB' scenario which is the ideal scenario. This graph is derivedfrom graph 6.5a by dividing the SINRs of all other scenarios by the SINR of the `NoHeNB' scenario, since it's the one with the highest SINR and behaves as the benchmarkfor other schemes. Here the random scheme has achieved 96% of relative SINR. `95%',`90%', `85%' and `Fixed' schemes have achieved percentages of 89.52%, 82.62%, 77.29%and 46.77% respectively. Out of these 5 schemes, clearly the Random PRB Selectionscheme has performed better compared to `95%', `90%' and `85%' power control schemes.

In relative SINR comparisons of `95%', `90%' and `85%' power control schemes with`Fixed' transmit power, three power control scenarios have outperformed the `Fixed' powerscenario with margins of 42.75%, 35.85% and 30.52% which shows a clear improvementover the worst case scenario. This justi�es the ability of the power control scheme tomitigate interference. Although the Random PRB selection scheme performs even betterin this regard, the throughput of the HUE might get hampered because this scheme onlyallocates 5 PRBs to HeNB users.

Ideally the three power control schemes should have had relative SINRs of 95%, 90%and 85%. It can be observed here that `95%', `90%' and `85%' power control schemeshave performed below than they are supposed to by margins of -5.48%, -7.38% and -7.71% respectively from the ideal relative SINR. The reason for this ine�ciency can beattributed to the presence of fading. For the estimation of received power at the MUE(from the HeNB and the eNodeB), HeNB considers only the e�ect of transmit power andpath loss as elaborated in section 3.2.1.5. Hence it should be mentioned that fading playsa vital part on the reduced e�ciency of the power controlling algorithm.

There's a guaranteed rate that the GBR user applications must satisfy, otherwise therewill be extra delays which deteriorates user satisfaction. VoIP is an example for such aGBR service which is a real time application that is sensitive to such delays. Usually anapplication end-to-end delay of more than 150 ms results in bad call quality [4]. Graph 6.5c



presents the mean end-to-end delays of VoIP macro UEs in six simulation scenarios. Thesigni�cant fact is that all the interference mitigation schemes have values less than 150 mswhile the `Fixed' transmit power scenario shows macro users having very bad call qualitywhich is much higher than 150 ms. This clearly indicates the performance enhancementin the VoIP application of the macro users due to interference alleviation.

As shown in �gure 6.3 Mean Opinion Score values depend on the end-to-end delays andthe delay jitter of VoIP users. Hence MOS is also an important metric on the performanceof the VoIP application. The mean values of MOS scores are presented in graph 6.5d.Graph 6.5e represents the the relative MOS percentages compared to the ideal case, `NoHeNB' scenario. Any improvement of SINR at the macro UEs due to the mitigation ofinterference should �nally re�ect on the performance of the user's application. MOS valuesalso give a clear indication on the performance enhancement of the VoIP application underthe two interference mitigation schemes over 'Fixed' scenario. Here, the Random PRBSelection scheme is closer to the ideal scenario with 99.5% relative MOS percentage with'95%' power control scheme having the next best value.



0

2

4

6

8

10

12

NoHeNB

Random 95% 90% 85% Fixed

SIN

R (

dB)

(a) Mean values of SINR of VoIP users

Random 95 90 85 Fixed0

20

40

60

80

100

SIN

R (

%)

(b) Percentage of SINR of VoIP users comparedto `No HeNB'

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

NoHeNB


End

−to

−en

d de

lay

(s)

(c) Mean values of end to end delay of VoIP users

0

1

2

3

4

5

NoHeNB


MO

S

(d) Mean values of Mean Opinion Score of VoIPusers


20

40

60

80

100

MO

S (

%)

(e) Percentage of MOS of VoIP users comparedto `No HeNB'

Figure 6.5: SINR, end-to-end delay and MOS values of VoIP users



6.4.2 FTP User Results

Results collected for FTP users are SINR and download response time. These valuesare collected across ten simulations for six scenarios and mean values of these results areplotted here with a 95% con�dence interval.

Graph 6.6a represents mean SINR values of FTP users for the six simulation scenariosnamely, `No HeNB', `Random', 95%, 90% and 85% sensitivity power control and �nally`Fixed' transmit power scheme. Graph 6.6b gives the percentages of mean SINR for FTPusers of other �ve scenarios compared to the `No HeNB' scenario. Here Random PRBSelection scheme achieves 97.17% and the three power control scenarios with sensitivitiesof 95%, 90% and 85% achieve 90.25%, 81.44% and 76.19% respectively while the �xedtransmit power scheme achieves 58.25%. This clearly shows the two interference mitigationschemes perform better compared to `Fixed' transmit power in terms of SINR.

The HeNB Power Control scheme shows reductions than the theoretical maximums,95%, 90% and 85% for the relative SINR values of macro users. This is because of thepresence of fading at the macro UE. HeNB does not include fading in the calculation ofreception powers from HeNB and other eNodeBs. Although the Random PRB Selectionscheme gives a very high relative SINR, the HeNB users of that scheme are only allocated5 PRBs. Therefore the HUEs of that scheme have a lower throughput compared to theHUEs of other schemes.

The non-GBR bearers usually carry non real time or best e�ort kind of services andFTP is an example for such a service. Hence FTP does not have high delay requirementsin contrast to real time or GBR services. Figure 6.6c depicts the mean download responsetimes of FTP users across the six scenarios. As expected, the download response time ofthe scheme `Fixed' transmit power has the highest delay with 8.31s delay and the idealscenario `No HeNB' has the lowest with 6.19s delay. HeNB Power Controlling schemes'and Random PRB Selection scheme's download response times lie between those of `NoHeNB' and `Fixed' scenarios.

Download response time for a certain �le represents the time taken for a download tocomplete since the request for that �le is sent. Hence download response time is a metricthat measures the total delay of a �le download in an FTP application. As the resultsshow this delay depends on the SINR of the user. Since the two interference mitigationschemes have reported lower download response times, than the 'Fixed' transmit powerscheme, this shows that the two interference mitigation schemes have done well to increasethe SINR and as a result the response time of the application has improved.



0

2

4

6

8

10

12

NoHeNB


SIN

R (

dB)

(a) Mean values of SINR of FTP users


20

40

60

80

100

SIN

R (

%)

(b) Percentage of mean SINR for FTP users com-pared to `No HeNB'

0

2

4

6

8

10

NoHeNB


Dow

nloa

d re

spon

se ti

me

(s)

(c) Mean values of download response time ofFTP users

Figure 6.6: SINR and download response time values of FTP users

6.4.3 Video User Results

Results that are collected for Video users are SINR and end-to-end delay which arecollected across 10 simulations for 6 scenarios, `No HeNB', `85%', `90%', `95%', `Random'and `Fixed'. Mean values of these results are plotted here with a 95% con�dence interval.

Bar Graph 6.7a depicts mean SINR values of video users for the six scenarios men-tioned above. From this, graph 6.7b is derived by dividing values of last �ve columns fromthe values of the �rst column. The reason is that the �rst column consists of values ofthe ideal scenario `No HeNB' and the derived values can be used to make a comparisonof the two interference mitigation schemes against `Fixed' transmit power scheme. Graph6.7b shows that HeNB Power Control scheme with sensitivities 95%, 90% and 85% providerelative SINR percentages of 82.49%, 73.52%, 67.74% and `Fixed' transmit power only has54.15% SINR compared to `No HeNB'. Hence there's clearly an SINR gain of HeNB powercontrol scheme over `Fixed' transmit power. `Random' PRB selection scheme performsbest with 97.42% SINR percentage which is closer to the ideal 'No HeNB' scenario.

The relative SINR values of the HeNB Power Control scheme show reductions thantheir theoretical maximums, 95%, 90% and 85%. This is again due to fading present atthe macro UE which is not estimated by the HeNB in HeNB and eNodeB reception powercalculations. Although the Random PRB Selection scheme gives a very high relative SINR



the HeNB users su�er because they are only allocated 5 PRBs. Hence they have a lowerthroughput compared to the HUEs of other schemes.

Figure 6.7c illustrates mean end-to-end delays of video users. As seen in the �gure`Fixed' transmit power scheme has the highest delay of 1s and the con�dence interval isalso higher suggesting a higher variation of delays. Mean end-to-end delays of all otherscenarios are less than 0.2s and a much lower delay variation suggesting a clear improvementover `Fixed' transmit power. This indicates how a relative SINR around 54% a�ects theend-to-end delays pretty badly for 'Fixed' scenario's macro users again emphasizing theimportance of the interference mitigation schemes.

0

2

4

6

8

10

12

NoHeNB


SIN

R (

dB)

(a) Mean SINR values of video users


20

40

60

80

100

SIN

R (

%)

(b) Mean relative SINR values of video users

0

0.5

1

1.5

2

2.5

NoHeNB


End

−to

−en

d de

lay

(s)

(c) Mean values of end to end delay of video users

0

0.2

0.4

0.6

0.8

1

1.2

1.4

NoHeNB


End

−to

−en

d de

lay

(s)

(d) Mean values of end to end delay of video users(without con�dence interval)

Figure 6.7: SINR and end-to-end delay values of video users

6.4.4 Throughput comparison of HeNB users

This section focuses on the performance of the HeNB users in terms of Uu throughput,the throughput of the air interface between the HeNB and its user and the number of PRBsused under the two interference mitigation schemes. The motivation for this analysis isthat although the Random PRB Selection scheme provides very good results for the macrousers inside the HeNB interference area, the number of PRB allocations for the HeNB usersare restricted to only �ve random PRBs. Hence the throughput of those HUEs might geta�ected. This section analyzes this aspect of the Random PRB Selection scheme whilemaking comparisons to the HUE throughput of the HeNB Power Control Scheme.



95% 90% 85% Random0

5

10

15

20

25

No.

of

PRB

s

HUE 1HUE 2HUE 3HUE 4

(a) PRB comparison of HUEs for '95%','90%','85%' and 'Random' scenarios

95% 90% 85% Random0

2

4

6

8

10

12

14

16

18

20

Thr

ough

put (

Mbp

s)

HUE 1HUE 2HUE 3HUE 4

(b) Throughput comparison of HUEs for '95%','90%','85%' and 'Random' scenarios

Figure 6.8: �g:HUE's PRB usage and throughput comparison

There are in total four scenarios chosen for comparisons, three from the HeNB PowerControl scheme, with 95%, 90% and 85% SINR reduction and one scenario from RandomPRB selection scheme con�gured to have a subset of �ve random PRBs for user allocationsand an interval of ten TTIs for randomizing the PRBs again.

As mentioned in section 6.1, there are four HeNB users in all the scenarios, all con-�gured with the video application having a data rate of 18 Mbps. As mentioned earlier,the motivation for con�guring the HUEs with a high data rate is to provide maximuminterference on the macro UEs in all the PRBs. All the parameters used for the scenariosmentioned here are con�gured with similar values to what's used in section 6.1.

Figures 6.8a and 6.8b represent respectively the no. of used PRBs and the throughputof four HUEs for the four scenarios mentioned here. As expected the no. of PRBs andthroughputs of the Random PRB Selection scheme are less than the others in the fourscenarios. The other signi�cant fact is the throughputs and the no. of used PRBs of theHeNB Power Control scheme have similar values in all four scenarios.

Hence it is evident that the performance of HUEs are limited in the Random PRBSelection scheme due to the limited number of PRB usage. On the other hand HeNBPower Control scheme is a much balanced scheme that mitigates macro UE interferencewhile being able to provide a better service to the HeNB users.

6.4.5 Behavior of HeNB Power Control Scheme near to the eNodeB

So far in the previous sections result comparisons for the two interference mitigationschemes were done for a speci�c situation where the HeNBs are 150 m away from thecentral eNodeB. The HeNB Power Control scheme relies on the estimated reception powerfrom the eNodeB and the HeNB at the MUE to mitigate interference. The in�uence offading is also not considered on this estimation. Hence it should be mentioned here thatthe actual eNodeB reception power at the MUE is a deciding factor on an accurate powercontrolling specially when the MUE is closer to the eNodeB. In this section an analysis onthe SINR of the MUE is performed with the HeNB Power Control Scheme in a scenariowhere the HeNBs are placed near to the eNodeB.

A HeNB to be placed at a distance of 150m can be considered as a mid distance froman eNodeB on a scenario where the inter cell distance is 500m, hence a question remainshow the HeNB Power Control scheme would behave when HeNBs are placed much closer



to the eNodeB. To analyze that, four HeNBs are chosen to be 85m away from the eNodeB.The minimum distance of a HeNB to an eNodeB is speci�ed as 35m by 3GPP [30]. Thedistance 85m is chosen here so that all four HeNBs are closer to the eNodeB and theinterference areas of the HeNBs are not overlapping with each other.

Chapter 4 explained how the interference areas of the HeNBs were generated in thisthesis. They are 100m × 100m square maps and the center point of a map lies where aHeNB is placed. For a better analysis of the SINR results it is important that the HeNBinterferences are not overlapping with each other.

Figure 6.9 shows how the HeNBs are placed around the eNodeB. eNodeB in the �gureis marked with a black dot in the center and a blue line marks the path of the MUE. Thereare four HeNBs, HeNB 1, HeNB 2, HeNB 3 and HeNB 4. There are �ve scenarios used forthe simulations, 'No HeNB', '95%', '90%', '85%' and 'Fixed'. Out of all these scenarios amacro user which gets really close to the eNodeB is chosen to see how the SINR behaves.The chosen macro user's path is shown in the blue line in �gure 6.9. The area where themacro UE's path intersects with the interference of HeNB 1 is chosen as the area to analyzethe behavior of the user's SINR.

Figure 6.10a depicts the mean SINR values of the �ve chosen scenarios at the inter-section point of the macro UE's path with HeNB 1 in �gure 6.9. Figure 6.10b shows therelative mean SINRs of the four scenarios '95%', '90%', '85%' and 'Fixed'. These relativevalues are obtained with respect to the SINR of the `No HeNB' scenario. The resultsindicate that the mean relative SINR of the 'Fixed' scenario is better than the other three.This means that the HeNB power control scheme has failed to reduce interference at theMUE at this instance. There are several factors that in�uence this behavior. One reason isthe presence of fading which is not estimated by the HeNB in received power calculation.

Figure 6.9: Macro UE path plot

This behavior can be further explained using three expressions that were used to derive



the HeNB transmit power in the HeNB Power Control scheme in chapter 3 as follows:

Expression 3.11 in chapter 3 gives the relationship of received SINR from the MUESINRWI , estimated eNodeB reception power Prx.eNB and estimated HeNB receptionpower Prx,HeNB at the macro UE,

SINRWI ≈Prx.eNB

IeNB,N + Prx,HeNB

where, IeNB,N is the interference from other eNodeBs plus noise at the macro UE. Ex-pression 3.12 shows the relationship of SINR without HeNB interference SINRWOI to theeNodeB received power,

SINRWOI =Prx,eNBIeNB,N

and expression 3.13 depicts the relationship of SINRWI and SINRWOI 3.13

SINRWI = SINR(x)WOI

where, x is the SINR reduction factor.Based on these three equations two expressions for Prx,HeNB and IeNB,N can be derived.

Prx,HeNB =Prx.eNB

SINR1/xWI

(6.3)

IeNB,N =Prx.eNBSINRWI

× (1− SINR1− 1x

WI ) (6.4)

When the estimation of Prx.eNB by the HeNB is higher than the actual eNodeB receptionpower at the MUE (this is because of fading as it makes the received power from theeNodeB to be considerably lower than the estimated value), the estimation of Prx,HeNBand IeNB,N also become higher than the actual values according to expressions 6.3 and6.4. Now the Prx,HeNB value, the estimated reception power from the HeNB at the MUEdetermines the transmit power of the HeNB according to equation 3.16,

Prx,HeNB =Ptx,HeNB

PLMUE,HeNB × Low

where, PLMUE,HeNB is the path loss between HeNB and macro UE and Low is the wallpenetration loss. As the reception power is over estimated, the transmit power also becomeshigher. This generates additional interference at the MUE. Because of this, the next SINRreport from the MUE will be further lower. This time the reason for lower SINR is the overestimation of HeNB transmit power. Hence the SINR reports from the MUE will continueto get lower as a cycle until Prx,HeNB gets less or equal than the actual HeNB receptionpower at the MUE.

This phenomena is more prominent when the UE and the HeNB are closer to theeNodeB which can be termed as a special case which the HeNB Power Control Schemehas not considered and a special solution in handling this is required to overcome thislimitation.


6.5. Conclusions

No HeNB 95 90 85 fixed0

5

10

15

20

25

30

35SI

NR

(dB

)

(a) SINR of HeNB Power Control scheme com-pared

95 90 85 fixed0

10

20

30

40

50

60

70

80

90

100

SIN

R (

%)

(b) Relative SINR of HeNB Power Controlscheme compared

6.5 Conclusions

In this chapter results of two novel interference mitigation schemes that were intro-duced by this work were analyzed, (HeNB Power Control with 95%,90% and 85% SINRreduction and Random PRB Selection). Results of these two schemes were comparedagainst an ideal case, where there's no interference from HeNBs and a worst case wherethere's maximum interference from HeNBs.

For the analysis, macro users were con�gured with three types of applications, VoIP,video and FTP. Under the two interference mitigation schemes it is observed that as theSINR of the macro users improve, performance of the user applications have also improvedcompared to the worst case situation.

Although Random PRB Selection Scheme performs better than HeNB Power ControlScheme regards to MUE SINR and the performance of user applications, HeNB users su�erbecause the HeNB allocates only a subset of PRBs to its users. On the other hand it canbe mentioned that HeNB Power Control Scheme provides a balanced performance to bothMUEs and HUEs as it not only e�ciently alleviates interference from MUEs but alsoprovides a good service to the HeNB users. The main issue with the HeNB Power Controlscheme is, as it's not able to estimate the amount of fading at the MUEs, the e�ciency ofinterference mitigation diminishes. The in�uence of fading to the accuracy of the HeNBPower Control Scheme is more prominent when the HeNB is closer to the macro eNodeB.

Finally it can be concluded according to the results that the two introduced interfer-ence mitigation schemes have been able to successfully mitigate interference at macro UEs.However both of them also have a few issues that require further attention.




7 Conclusions and Future Work

7.1 Outlook and Conclusions

The main contributions of this work are two novel interference mitigation schemes forfemtocell interference on macro users in LTE Advanced. First one, an analytical method,�HeNB Power Control Scheme� which is a simple yet e�ective scheme relies on CQI sig-nals from MUEs to alleviated interference. The second one, a PRB randomizing method,�Random PRB Selection Scheme� which is also a quite simple scheme that selects only asubset of random PRBs to allocate to HeNB users in order to create interference on themacro users only on that chosen subset of PRBs.

As the �rst task of this thesis, an extensive literature survey was conducted to searchfor the current state of the art on HeNB interference mitigation. The next phase in thethesis was the familiarization process of the OPNET simulation environment and ComNetsLTE-A system level simulator. The HeNB architecture was studied in the 3GPP speci�ca-tions and based on that a new model for HeNBs was implemented in the simulator includinga node model and a process model in the OPNET Modeler software. A path loss model, aslow fading model and a fast fading model was also implemented for HeNB users accordingto the 3GPP speci�cations in the simulator and the accuracy of these models were veri�edusing simulations. Then the two interference mitigation schemes were implemented in thesimulator and the accuracy of their functionality was veri�ed using simulations as well.Finally the performance of these two schemes were analyzed with an ideal scheme withoutHeNB interference and a worst case scenario of maximum HeNB interference.

Results indicate that the two interference mitigation schemes perform e�ciently com-pared to the worst case situation. Although Random PRB Selection Scheme performsbetter than HeNB Power Control Scheme with regards to MUE SINR and performance ofthe users' applications, the HeNB users su�er because the HeNB allocates only a subset ofPRBs to its users. In addition, in real life situations the cells can get more and more loadedwith MUEs and as a result when choosing a subset of PRBs, there might still be a highprobability that this subset would interfere with certain MUEs. On the other hand HeNBPower Control Scheme gives a balanced performance as it e�ciently alleviates interferenceon MUEs while providing a good service to the HeNB users. The main issue with theHeNB Power Control scheme is, as it's not able to estimate the amount of fading at theMUEs, the e�ciency of interference mitigation diminishes. The in�uence of fading to theaccuracy of the HeNB Power Control Scheme is more prominent when the HeNB is nearerto the macro eNodeB. This has to be further studied and a solution on how to deal withthese situations must be devised.

The two interference mitigation schemes have several novelties compared to the currentstate of the art with regards to the simplicity, less hardware intensiveness and no relianceon backhaul communication. As mentioned earlier most state of the art solutions focus oninband or out of band signaling and exchange of information, however these schemes donot require any of this which is a major plus since additional signaling has delay issues aswell as waste of time. HeNB Power Control Scheme in particular has more control over theamount of interference it should generate at the macro UE due to its analytical approach.As this method relies on UE measurements it is also capable of dynamically adaptingto changing interference conditions at random places. Comparatively the Random PRBSelection Scheme is a much simpler approach which provides very e�cient interferencemitigation with a slight reduction of performance at the HeNB users.

7. Conclusions and Future Work

7.2 Future Work

The work presented in this thesis can be extended and enhanced in some speci�careas. Random PRB Selection scheme requires an optimum combination for the numberof PRBs and TTIs using an additional sensitivity analysis and this can be performed tostudy the impact of the two parameters on the performance of the macro UEs so as to�nd the optimum settings for them. This optimum combination should be able to reduceinterference e�ciently at the macro users and also to provide a better service to homeusers. At the moment this scheme mitigates interference almost perfectly but the homeusers su�er with lack of PRB allocation.

HeNB Power Control scheme requires a solution for the SINR drop in the macro UEswhen the HeNBs are placed near to the eNodeB. It is also required to �nd a better solutionfor the estimation of the macro users' fading so as to enhance the accuracy of the scheme,especially when the HeNBs are closer to the eNodeBs.


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