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S P R I N G E R B R I E F S I N CO M P U T E R S C I E N C E
Duy Trong NgoTho Le-Ngoc
Architectures of Small-Cell Networks and Interference Management
SpringerBriefs in Computer Science
Series Editors
Stan ZdonikPeng NingShashi ShekharJonathan KatzXindong WuLakhmi C. JainDavid PaduaXuemin (Sherman) ShenBorko FurhtV.S. SubrahmanianMartial HebertKatsushi IkeuchiBruno Siciliano
For further volumes:http://www.springer.com/series/10028
Duy Trong Ngo • Tho Le-Ngoc
Architectures of Small-CellNetworks and InterferenceManagement
123
Duy Trong NgoSchool of Electrical Engineering
and Computer ScienceUniversity of NewcastleCallaghan, NSW, Australia
Tho Le-NgocDepartment of Electrical
and Computer EngineeringMcGill UniversityMontreal, QC, Canada
ISSN 2191-5768 ISSN 2191-5776 (electronic)ISBN 978-3-319-04821-5 ISBN 978-3-319-04822-2 (eBook)DOI 10.1007/978-3-319-04822-2Springer Cham Heidelberg New York Dordrecht London
Library of Congress Control Number: 2014932974
© The Author(s) 2014This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part ofthe material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,broadcasting, reproduction on microfilms or in any other physical way, and transmission or informationstorage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodologynow known or hereafter developed. Exempted from this legal reservation are brief excerpts in connectionwith reviews or scholarly analysis or material supplied specifically for the purpose of being enteredand executed on a computer system, for exclusive use by the purchaser of the work. Duplication ofthis publication or parts thereof is permitted only under the provisions of the Copyright Law of thePublisher’s location, in its current version, and permission for use must always be obtained from Springer.Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violationsare liable to prosecution under the respective Copyright Law.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoes not imply, even in the absence of a specific statement, that such names are exempt from the relevantprotective laws and regulations and therefore free for general use.While the advice and information in this book are believed to be true and accurate at the date ofpublication, neither the authors nor the editors nor the publisher can accept any legal responsibility forany errors or omissions that may be made. The publisher makes no warranty, express or implied, withrespect to the material contained herein.
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Preface
To accommodate the ever-increasing demand for mobile data, the wireless industryis facing with the urgent requirement of growing the capacity of mobile access net-works by 1; 000 times. The extreme densification of small cells is currently the bighope to resolve the unprecedent “1000� data challenge” and to provide ubiquitousnetwork coverage with an optimized grade of service. Small-cell heterogeneousnetworks represent a paradigm shift from the traditional centralized macrocellapproach to a more self-organized solution, where small cells are deployed inconjunction with existing large cells at all possible venues, indoors and outdoors,and in all types and sizes. However, the coexistence of different types of networkdevices with diverse specifications on the same spectrum raises a new set of majordesign issues. These critical challenges urgently need to be solved to fully realizethe promised benefits of small-cell solutions.
This SpringerBrief covers two important aspects of the emerging small-cellwireless heterogeneous networks. First, the architectures of small-cell networksare reviewed, with specific references to the current wireless network standards.Second, new adaptive power control and dynamic spectrum access techniques arediscussed to promote a harmonized coexistence of diverse network entities in both3G and 4G small-cell networks. Analytically devised from optimization and gametheories, these autonomous solutions are shown to effectively manage the severeintra-tier and cross-tier interferences in small cells. The target audience of thisinformative and practical SpringerBrief is researchers and professionals working inwireless networking and interference management. The content is also valuable foradvanced-level students interested in network communications and radio resourceallocation.
We would like to acknowledge the financial supports from the Natural Sciencesand Engineering Research Council of Canada and the Alexander Graham BellCanada Graduate Scholarship.
Finally, we dedicate this work to our families.
Callaghan, NSW, Australia Duy Trong NgoMontreal, QC, Canada Tho Le-Ngoc
v
Contents
1 Dense Small-Cell Networks: Motivations and Issues . . . . . . . . . . . . . . . . . . . . 11.1 Mobile Data Traffic and Indoor Coverage Challenges . . . . . . . . . . . . . . . . 11.2 Extreme Network Densification Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.1 Frequency Reuse Principle and Cellular WirelessNetworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.2 Small-Cell Heterogeneous Network Deployment . . . . . . . . . . . . . 51.2.3 Technical Challenges in Small Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3 Structure of the Brief. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2 Architectures and Interference Managementfor Small-Cell Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.1 Requirements and Reference Model for Small-Cell
Network Architectures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2 Small-Cell Architectures in Wireless Network Standards . . . . . . . . . . . . 13
2.2.1 3GPP UMTS Small-Cell Architecture . . . . . . . . . . . . . . . . . . . . . . . . . 132.2.2 3GPP LTE Small-Cell Architecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.2.3 3GPP2 CDMA2000 1x Small-Cell Architecture . . . . . . . . . . . . . . 162.2.4 Air Interfaces: CDMA vs. OFDMA .. . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.3 Interference Management in Small-Cell Networks. . . . . . . . . . . . . . . . . . . . 182.3.1 Interference Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182.3.2 Power Control for CDMA-Based Wireless Networks . . . . . . . . 192.3.3 Joint Subchannel-Power Allocation in OFDMA Networks. . . 23
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3 Distributed Interference Management in HeterogeneousCDMA Small-Cell Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333.1 System Model and Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343.2 Distributed Joint Power and Admission Control Algorithms . . . . . . . . . 37
3.2.1 QoS Guarantee for MUEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.2.2 Dynamic Pricing, Power Adaptation and
Admission Control for FUEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
vii
viii Contents
3.3 Practical Implementation Issues and Further Extensions . . . . . . . . . . . . . 443.3.1 Communication Overhead of Proposed Algorithms . . . . . . . . . . 443.3.2 Improving Efficiency of Equilibrium Solutions . . . . . . . . . . . . . . . 44
3.4 Illustrative Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4 Distributed Pareto-Optimal Power Control for UtilityMaximization in Heterogeneous CDMA Small-Cell Networks . . . . . . . . . 514.1 System Model and Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524.2 Distributed Power Control for Joint Utility Maximization
with Macrocell QoS Protection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564.2.1 Pareto-Optimal SINR Boundary and Approximate
Solution via Log-Barrier Penalty Method . . . . . . . . . . . . . . . . . . . . . 564.2.2 Distributed Algorithm for Globally Maximized
Joint Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 594.3 Distributed Power Control for Femtocell Utility
Maximization and Macrocell SINR Balancing . . . . . . . . . . . . . . . . . . . . . . . . 604.3.1 Distributed Pareto-Optimal SINR Assignment . . . . . . . . . . . . . . . . 614.3.2 Distributed Algorithm for Femtocell Utility
Maximization and Macrocell SINR Balancing . . . . . . . . . . . . . . . . 644.3.3 Advantages of FUM-MSB Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.4 Illustrative Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
5 Joint Power and Subchannel Allocation in HeterogeneousOFDMA Small-Cell Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 735.1 System Model and Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745.2 An Iterative Approach to Joint Power and Subchannel Allocation . . . 77
5.2.1 Feasibility and Initial Feasible Allocation . . . . . . . . . . . . . . . . . . . . . 785.2.2 Optimal Subchannel Assignment for Fixed Power
Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 795.2.3 Optimal Power Allocation for Fixed Subchannel
Assignment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 805.3 Proposed Joint Power and Subchannel Allocation
Algorithms with Macrocell Total Throughput Protection . . . . . . . . . . . . . 855.3.1 Centralized SCA-based Power Allocation with
AGM Approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865.3.2 Distributed SCA-based Power Allocation
with Logarithmic Approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 875.3.3 Distributed SCA-based Power Allocation with
D.C. Approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905.4 Illustrative Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Contents ix
6 Distributed Resource Allocation in OFDMA CognitiveSmall-Cell Networks with Spectrum-Sharing Constraints . . . . . . . . . . . . . . 996.1 System Model and Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1006.2 Joint Subchannel and Power Allocation for Throughput
Maximization in Cognitive Femtocell Networks . . . . . . . . . . . . . . . . . . . . . . 1046.2.1 Optimal Design with Spectrum-Sharing Constraints . . . . . . . . . 1046.2.2 Distributed Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.3 A Dual Approach to Power-Efficient Resource Allocation . . . . . . . . . . . 1106.4 Reduced-Complexity Schemes for Throughput Maximization . . . . . . . 1126.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6.5.1 Asymptotic Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1136.5.2 Illustrative Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Acronyms
1-D One-dimensional2-D Two-dimensional3G Third generation3GPP Third Generation Partnership Project3GPP2 Third Generation Partnership Project 24G Fourth generationAGM Arithmetic-geometric meanAWGN Additive white Gaussian noiseBER Bit error ratebps Bit per secondBS Base stationCDMA Code-division multiple accessCINR Channel-to-interference-plus-noise ratioCN Core NetworkCoMP Coordinated multipoint transmission and receptionCR Cognitive radioCSMA/CA Carrier-sense multiple access with collision avoidanceD.C. Difference-of-two-concave-functionsDSL Digital subscriber lineEPC Evolved Packet CoreFDMA Frequency-division multiple accessFFT Fast Fourier transformFUE Femtocell user equipmentGSM Global System for Mobile CommunicationsHeNB Home evolved Node BHSPA High Speed Packet AccessICI Intercell interferenceIEEE Institute of Electrical and Electronics EngineersIP Internet ProtocolIS-95 Interim Standard 95KKT Karush-Kuhn-Tucker
xi
xii Acronyms
LTE Long Term EvolutionMNO Mobile network operatorMUE Macrocell user equipmentNE Nash equilibriumNP Non-deterministic polynomial-timeOAM Operation, administration and managementOFDM Orthogonal frequency-division multiplexingOFDMA Orthogonal frequency-division multiple accessPSD Power spectral densityPU Primary userQoS Quality of serviceRNC Radio Network ControllerRx ReceiverSC Single-carrierSCA Successive convex approximationSINR Signal-to-interference-plus-noise ratioSNR Signal-to-noise ratioSU Secondary userTx TransmitterUE User equipmentUMTS Universal Mobile Telecommunications SystemUTRAN Universal Terrestrial Radio Access NetworkVNI Visual Networking IndexWCDMA Wideband code-division multiple accessWiMAX Wireless Interoperability for Microwave Access