2005:238 CIV

M A S T E R ' S T H E S I S

Improved Power Controlfor GSM/EDGE

Fredrik Hägglund

Luleå University of Technology

MSc Programmes in Engineering

Department of Computer Science and Electrical EngineeringDivision of Signal Processing

2005:238 CIV - ISSN: 1402-1617 - ISRN: LTU-EX--05/238--SE

Improved Power Control

for GSM/EDGE

Fredrik Hägglund

11th February 2005

Abstract

In GSM (Global System for Mobile Communication), a tradeoff betweendifferent goals is necessary to achieve the optimal system performance. Gen-erally, high speech quality, high capacity and low power consumption aremajor goals. Power control is one of several techniques used to reach thesegoals. Power control regulates the signal strength with the aim to reducethe overall interference. Since radio environment and mixture of differentuser requirements may vary, there is an interest in making the setting ofthe power control target value automatically and dynamically. The targetvalue should adapt to the environment and the situation. The method usedis to extend the current power control with an outer loop that could adjustthe quality parameter qdes. An attempt to use EMR data to adjust qdes isshown to have effects that eliminate the essential principle of power backoffto avoid the so called party effect, and is therefore not recommended.

However, a method using the distribution of the transmitted power in-dicates more promising results. It is shown that there is high correlationbetween the number of satisfied users and the number of users within theregulating window, i.e. the number of users not limited by the maximum orminimum power levels.

Acknowledgement

This Master’s Thesis is the final part of my Master of Science Degree inSignal Processing at Luleå University of Technology. The work has beencarried out at Ericsson Research in Luleå during fall 2004.

First I would like to thank my supervisor Magnus Thurfjell at Ericssonfor great guidance and valuable support during the Thesis. I would also liketo thank my examiner James LeBlanc at Luleå University of Technology forhis work.

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Contents

1 Introduction 1

1.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.4 Delimitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.5 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2 Background 3

2.1 Evolution of cellular networks . . . . . . . . . . . . . . . . . . 32.2 The GSM network . . . . . . . . . . . . . . . . . . . . . . . . 42.3 Radio network . . . . . . . . . . . . . . . . . . . . . . . . . . 52.4 Impairments to radio transmission . . . . . . . . . . . . . . . 7

2.4.1 Fast fading . . . . . . . . . . . . . . . . . . . . . . . . 72.4.2 Path loss . . . . . . . . . . . . . . . . . . . . . . . . . 82.4.3 Shadow fading . . . . . . . . . . . . . . . . . . . . . . 82.4.4 Time dispersion . . . . . . . . . . . . . . . . . . . . . 82.4.5 Co-channel interference . . . . . . . . . . . . . . . . . 8

3 Power control 9

3.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93.2 Current power control algorithm . . . . . . . . . . . . . . . . 103.3 EMR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133.4 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . 13

4 Simulator description 14

4.1 Simulation model . . . . . . . . . . . . . . . . . . . . . . . . . 144.2 Basic functionality . . . . . . . . . . . . . . . . . . . . . . . . 16

4.2.1 Propagation model . . . . . . . . . . . . . . . . . . . 164.2.2 Fast fading . . . . . . . . . . . . . . . . . . . . . . . . 164.2.3 Frequency hopping . . . . . . . . . . . . . . . . . . . 174.2.4 Discontinuous transmission . . . . . . . . . . . . . . . 174.2.5 Quality estimation . . . . . . . . . . . . . . . . . . . . 18

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5 Tested algorithms 20

5.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205.2 Parameter settings . . . . . . . . . . . . . . . . . . . . . . . . 215.3 Outer loop based on EMR . . . . . . . . . . . . . . . . . . . . 22

5.3.1 Outer loop based on frame erasure rate . . . . . . . . 225.3.2 Outer loop based on coefficient of variation . . . . . . 255.3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . 28

5.4 Outer loop based on power distribution . . . . . . . . . . . . 285.4.1 Power distribution analysis . . . . . . . . . . . . . . . 285.4.2 Simulated algorithm . . . . . . . . . . . . . . . . . . . 35

6 Discussion 39

6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396.2 Further studies . . . . . . . . . . . . . . . . . . . . . . . . . . 40

A List of Abbreviations 42

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List of Figures

2.1 Simple schematic view over the GSM hierarchy. . . . . . . . . 52.2 A 4/12 frequency reuse pattern. The gray cells are using the

same frequency group and hence mobiles from these cells usingthe same frequency could interfere with each other. . . . . . . 6

3.1 Transmission power p1 and p2 from base stations to mobilestations. Each mobile experience a carrier signal power Cand interference I. . . . . . . . . . . . . . . . . . . . . . . . . 10

3.2 Principle for down regulation. The values rxlev and rxqualare the measured values before any exponential filtering. . . 12

4.1 Schematic view of the FHRUNE simulator. . . . . . . . . . . 154.2 Format of the frequency hopping matrix. . . . . . . . . . . . . 174.3 The steps in the mapping from C/I to FER. . . . . . . . . . 184.4 The lookup table for mapping mean and standard deviation

to FEP shown as a figure. . . . . . . . . . . . . . . . . . . . 19

5.1 The existing power control in GSM extended with the outerloop. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

5.2 Block scheme for the existing power control algorithm ex-tended with an outer loop based on EMR. . . . . . . . . . . 22

5.3 The outer loop when the control algorithm is based on FER. 235.4 Satisfied users at different traffic loads. . . . . . . . . . . . . 255.5 BER and CV of BER is plotted against each other. Every

dot gives the BER and CV of BER for each mobile at eachmeasurement time. An approximation of a level curve forFER_target = 1% is also in the figure. . . . . . . . . . . . . 26

5.6 A plot over how CV_BEP changes around the average linefor one single mobile during a call. The call lasts for nearly 7seconds and it is impossible to see a trend for the CV_BEPvalues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

5.7 Histograms for two different occasions. In the left plot thesystem has experienced a relatively low traffic load and in theright a relatively high traffic load. . . . . . . . . . . . . . . . 30

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5.8 Number of satisfied users for a specific condition for differentqdes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

5.9 The usage of power control and the amount of satisfied usersplotted for different qdes. The traffic load is fixed and low. . 32

5.10 The plot shows the regulating fraction of the transmitted pow-ers and the number of satisfied users for a high traffic load.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.11 The plot shows the regulating fraction of the transmitted pow-ers and the number of satisfied users for a high traffic load.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

5.12 The difference between number of mobiles transmitting onmaximum effect and the number of mobiles transmitting onminimum effect for some different traffic loads. . . . . . . . . 35

5.13 A block scheme of the outer loop based on the usage of powercontrol. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

5.14 The qdes value is adjusted to a proper value, depending onthe current environment in the cell. . . . . . . . . . . . . . . 37

5.15 The number of satisfied users with and without an outer loopin the power control. The result with no power control is alsodisplayed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

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Chapter 1

Introduction

This section will give a brief introduction to the subject handled in this work.The purpose, method and the delimitations are also in this section. Finally,an outline for the report is presented.

1.1 General

GSM (Global System for Mobile Communication) is a mobile system that isglobally used. In GSM, and in other traditional mobile systems a tradeoff be-tween different goals is necessary to achieve the optimal system performance.Generally, high speech quality, high capacity and low power consumption aremajor goals in cellular radio communication systems. Power control is oneof several techniques used to achieve these goals. Power control regulatesthe signal strength to reduce the overall interference.

One of the parameters that control the power level are a target valuecontrolling the desired quality. Instead of setting this target value for eachseparate case, for example different radio environment or speech codecs, thereare some benefits in making the control of this target value automatic. Howthe target value should be set may depend on many variables, such as theinterference from other cells, the distance between the mobile station andthe base station, the traffic load, the total amount of radiated power etc.

Therefore, there is an interest in making the setting of the target valueautomatic and dynamic.

1.2 Purpose

The purpose of this work is to find out whether a method, based on theadditional information from for example the new standardized measurementreport, could improve the current power control by reducing the hard param-eter predefinitions. This could be done by making it possible to set the targetvalue automatically. The method should improve, or at least preserve the

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performance of the existing power control. The results of the work includesrecommendations on algorithm design, parameter tuning and comments ofperformance in general.

1.3 Method

The method chosen to fulfill the purpose was to automatically adjust thetarget value in an “outer loop”, using additional information from for ex-ample the enhanced measurement report. Initially some analysis was done,principally about how information concerning speech quality should be used,but also what kind of information to use. Several different fundamental algo-rithms have been developed and a simple evaluation determines whether thealgorithms have been excluded or if they were relevant for further analysis.A model has been made for each of the relevant algorithms, which showshow the additional information controls the desired target value. Adjustingthe signal strength to track this target value sets the desired speech quality.

Input values, which are decided from the outer loop, that adjusts thesignal strength have been tested and evaluated. This means that simulationshave been done to verify the choices of input values in different situations. Itshould be easy to change the input values. The simulation tool that has beenused is an advanced existing simulator at Ericsson Research called FHRUNE.

1.4 Delimitations

The work was delimited to only look at an outer loop that controls the qual-ity target value, which is an input to the existing power control algorithm.This means that there are possibilities that other solutions could give betterperformance for the outer loop. But such algorithms have not been examinedin this work.

Another limitation was to only look at speech transmission and notpacket data transmission.

1.5 Outline

In chapter two the background to the subject will be presented. Chapterthree describes the existing power control algorithm, and a problem state-ment that will more precisely describe the problem. In chapter four thesimulation model is described and how the simulations where done to modelthe different approaches of the outer loop will be presented in chapter five.The results of the simulations and an analysis of the results will also be pre-sented in chapter five. Finally, in chapter six a discussion is presented withthe conclusions and some ideas about future work.

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Chapter 2

Background

The background theories about mobile systems, the GSM system, radio net-work and impairments to radio transmission are presented briefly in thissection to give an initial understanding.

2.1 Evolution of cellular networks

The first generations cellular networks (1G) were analogue systems launchedin the beginning of the eighties. Examples are NMT450 and NMT900(Nordic Mobile Telephone), TACS (Total Access Communication System)in United Kingdom and AMPS (Advanced Mobile Phone Service) in USAand Canada. All these systems where using Frequency Division MultipleAccess (FDMA). In FDMA each user has a dedicated frequency and henceonly one user per channel is allowed.

In the beginning of the nineties the second generation cellular systems(2G) were developed. Examples of systems are GSM (Global System forMobile Communication), D-AMPS (Digital-Advanced Mobile Phone Service)in America and PDC (Personal Digital Cellular) in Japan. The 2G systemswere improved with both digital transmission and Time Division MultipleAccess (TDMA). In TDMA users are sub-divided into a number of time slotsfor each carrier frequency. For example, the GSM system uses both FDMAand TDMA, where users are still assigned to a discrete slice of the frequencyspectrum, but these are divided into eight time slots (full-rate GSM). GSMwas designed for voice, but with data capabilities. [2]

The third generation cellular system (3G) was launched first in 2001. 3Gare designed for data, but with voice capabilities and allow different multi-media services at very high bit rates. GPRS (General Packet Radio Services)is a developed version of GSM and the first step towards the third genera-tion. Other systems developed against 3G are GSM/EDGE (Enhanced Datarates for GSM Evolution) and WCDMA (Wideband Code Division Multi-ple Access). 3G are planned to be the key system for future multimedia

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communication worldwide.

2.2 The GSM network

The GSM system was introduced to the European market in 1991. It is themost widely spread of the 2G standards. GSM is active on the frequencyband around 900 MHz. As said before, GSM uses both FDMA and TDMA.The GSM system is using a number of 200 kHz FDMA channels, each onedivided into eight TDMA timeslots for speech transmission [4]. Each of theeight time slots has duration of 0.577 ms. Binary Gaussian Minimum ShiftKeying (GMSK) is used as the modulation technique, which provides oneinformation bit per symbol. This could be compared with 8 PSK (Phase ShiftKeying) that is used in for example EDGE that provides three informationbits per symbol. EDGE is developed from GSM and GPRS to support muchhigher data rates. [2]

In the transmitter, the analog speech is digitized and divided into seg-ments of 20 ms, called a frame. GSM digitize the speech by using an 8 kHzsampling frequency and 8 bits resulting in a bit rate of 64 kbps. The bitstream has been compressed and quantized by using a mix of a vocoder anda waveform coder, resulting in a 13 kbps bit stream. There are also someburst formatting, channel coding and interleaving before the information istransmitted on a time slot. A sequence of bits sent during one time slot iscalled a burst and each speech frame is spread over eight bursts.

The GSM radio network is built up with Base Transceiver Stations (BTS)in a cellular structure. The BTS consists of a group of transmitters andreceivers that communicate with the mobile stations (MS) located in thecell that it controls. The communication to different mobile stations takesplace in different channels, divided up as described above. The next levelin the network is the Base Station Controller (BSC), which communicateswith one or more BTS. In other words, the BTS has the radio equipmentfor example antennas and transmitters that makes it possible for the BSC tocommunicate with the mobile stations. The BSC is in charge of hand overs,what transmit powers to use and other higher level tasks. The next stepin the traditional GSM hierarchy is the Mobile services Switching Center(MSC). The MSC sets up, supervises and releases calls. This is a big switchthat interfaces several BSC, via a Gateway MSC (GMSC), to other telephonyand data systems such as PSTN (Public Switched Telephone Network) orother networks. In Figure 2.1 there is an overview of the GSM hierarchy. [5]

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GMSC

PSTN

MSC

BSC

BTS BTS

MS

MS MS

MS

Figure 2.1: Simple schematic view over the GSM hierarchy.

2.3 Radio network

The basic components in a radio network are the mobile station, the basestation that communicates with the mobile station, and the mobile switchingcenter, which sets up, controls and releases calls. All base stations controldifferent areas, also known as cells. Each cell has one base station thatmobile stations in that cell could connect to. However, several base stationare usually placed at one single site depending on the cellular structure.Normally a cell structure of three base stations per site is used. A cell canbe of any size from a radius of tens of meters to a radius of tens of kilometers.[1]

The transmission between the base station and the different mobiles ina cell takes place in a set of channels, for example based on the number offrequencies. Mobile systems only have a limited amount of bandwidth. Eachuser requires a certain amount of that bandwidth. If each frequency onlywere used once, also the number of users would be limited. This means that

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frequencies used in one cell need to be reused in another cell at a certaindistance away. Users that use the same frequency will interfere with eachother. A group of cells that together uses all the available frequencies inthe system is called a cluster of cells. Clusters repeated over and over againforms a cellular network. A schematic illustration of a cellular network isseen in Figure 2.2, where the cells are represented as hexagons for simplicity.The frequencies used in a cluster are divided into frequency groups. Howmany frequencies there are in each group is dependent on the total number ofavailable frequencies and the required reuse factor. Different reuse patternscan be formed but some examples are 4/12 or 3/9. For example, 4/12 meansthat all the available frequencies are divided into 12 frequency groups, onefor each cell, which is located at 4 sites with 3 base stations each. In a systemlike this the reuse factor is 12. As seen in the figure below each base stationsite has three cells and is using directional antennas. [2]

Figure 2.2: A 4/12 frequency reuse pattern. The gray cells are using thesame frequency group and hence mobiles from these cells using the samefrequency could interfere with each other.

It is preferable to keep the number of base stations down, to decreasecosts of the BTS hardware and expensive sites when establishing new basestations. The existing base stations should be used in the most efficient wayto avoid establishing new ones, including considerations about the limitedamount of bandwidth. The base stations that use the same set of frequenciesshould be placed at sufficient distance apart from each other to decreaseinterference. However, to keep the capacity at an acceptable level the basestations have to be relatively close to each other. So there will always besome interference.

The mobile stations in the gray cells in the Figure 2.2 above could ex-perience co-channel interference because of the reuse of frequency carrier.Cells that simultaneously uses the same carrier frequency interfere with eachother if they are close enough. To measure the amount of interference at

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a connection one measurement that could be used is the carrier to interfer-ence ratio (C/I). This measurement is the relation between the carrier signalpower C and the interference power I. The carrier signal power, in dB, forone connection is defined as

C(t) = p(t) + g(t), (2.1)

where p(t) is the transmitted power in the downlink and g(t) is the (nega-tive) gain between the mobile and the base station. The interference I(t)contains both of the interference carrier power from other base stations andthe thermal noise, see [3]. However, the interfering power from neighboringcells with the same carrier frequencies are above the noise floor. This meansthat the system is interference limited rather than noise limited. The C/I,in dB, for each mobile is defined as

C/I = C(t) − I(t) = p(t) + g(t) − I(t). (2.2)

Suitable ranges for this parameter are decided by the desired qualityprofile. For example acceptable speech quality or required data bit rate.However, a high C/I-value corresponds obviously to a high quality in thespecific connection [3].

2.4 Impairments to radio transmission

The problem with radio transmission is that it is impossible to control thetransmission environment. The impairments are known, but their effect asa function of time is unpredictable and hence, it is difficult to accuratelymodel the transmission dynamically. There are several factors that affectradio transmission conditions, in addition to noise. Some of the problemswith radio transmission are described below [5].

2.4.1 Fast fading

One effect that could occur is that the reflected signals could arrive at thereceiver with such an unfavourable phase that they cancel out each other.This cancelling effect, which is also referred to as fast fading or Rayleighfading, is however dependent on the position of the transmitter or receiver,so that often it is already sufficient to change position by less than half awavelength. Moreover, fading also depends on the transmitter frequencywhich influences the phase of the signals at the reception site. This meansthat the fading dips will appear at different places for different frequencies.This fading effect is most common where the reflecting is high.

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2.4.2 Path loss

The amplitude of a signal diminishes when a signal travel further away fromthe transmitter. This phenomenon is referred to as path loss. Path loss canmake it difficult to get enough signal strength in a large cell. An advantagewith path loss is the natural decrease in interference from other cells. Thisis the principle on which the reuse in a cellular system is built.

2.4.3 Shadow fading

Another fading impairment, except for fast fading, is shadow fading or some-times called slow fading or log normal fading. Obstacles, that are shadowingthe radio path between the transmitter and receiver, will cause slow varia-tions in signal strength. Anything interrupting the free line of sight couldbe considered as an obstacle.

2.4.4 Time dispersion

A reflecting object far away, such as a mountain, reflects signals and themobile station will hence receive both a direct radio signal and a fairly strongreflected signal from the reflecting object. These two signals will arrive atdifferent times which could cause individual bits to overlap with each otherand disturb the overall received signal. This effect is called Inter SymbolInterference (ISI).

2.4.5 Co-channel interference

Distant radio transmitters transmitting on the same frequency as the oneused by a special radio link will disturb. Even if they are very far away andtheir amplitude has been attenuated due to path loss a disturbing effect willbe noticed in the receiver. This impairment is known as co-channel interfer-ence and is an important part in mobile networks. Co-channel interferenceis described more deeply in other parts in this report.

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Chapter 3

Power control

This chapter describes power control in general and the existing power con-trol algorithm. A description of the EMR (Enhanced Measurement Report)is also presented. The chapter ends with a discussion about the problem andhow the problem might be solved.

3.1 General

Power control (PC) refers to the strategies or techniques required to adjustthe transmitted power. Power control regulates the transmitted power toachieve a desired signal strength. A mobile far away from a base stationrequires a stronger transmitted signal than a mobile close to a base station. Ifthe speech quality is better than necessary for one mobile the signal strengthfor that specific mobile will be decreased. This implies that the system willbe improved, because of the reduction in interference. The single mobile willalso experience a decrease in battery consumption when transmitting to thebase station. This is the main idea with power control. Power control isused both in uplink and in downlink between base station and mobile. Inthis work only downlink is described. The principle is however equal.

The transmission power p from the base station to the mobile, Figure3.1, should be controlled to optimize the system. The power should be highenough to achieve a sufficient carrier signal power C at the mobile stationand low enough to minimize interference I at other mobiles. The transmittedpowers from base stations to mobiles are controlled by the power controlalgorithm developed for the GSM network.

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C

I

C

I

p2

p1

Figure 3.1: Transmission power p1 and p2 from base stations to mobile sta-tions. Each mobile experience a carrier signal power C and interference I.

A common strategy to utilize available resources in cellular radio sys-tems is therefore to control the transmitter powers described above. Themotivation is to maintain an acceptable quality throughout the lifetime of aconnection, in other words an acceptable C/I. That is, the aim with powercontrol is to increase the number of mobile stations with a C/I on an accept-able level. The power control will optimize the transmitted power, and thusincrease the number of satisfied users if traffic is maintained, or keep the thenumber of satisfied users if traffic is increased [6]. When power control isused the total amount of radiated power is reduced compared to when it isnot used.

Keeping an acceptable level of quality should hold despite varying chan-nel conditions and presence of disturbing interference from other users. Theexisting power control algorithm considers the system quality and not thequality for single mobiles as the main regulate factor. This means that somesingle mobiles have to accept slightly worse quality to improve the total sys-tem quality. However, when applying power control to real systems, somechallenges are prevalent. Available information in measurement reports iscrude, highly quantized and constrained to physical limits. So one chal-lenge is to issue relevant power levels based on this information to obtain anacceptable quality. [3]

3.2 Current power control algorithm

In the power control algorithm, quality and signal strength is both consid-ered. Bad quality as well as low signal strength will increase the transmit-ted power. For each measurement period (480 ms) two variables, rxqualand rxlev, are reported based on measurement from all bursts during thatmeasurement period. The variables rxqual and rxlev stands for receivedquality and received signal strenght. These variables are used to adjust thetransmitted power. Predefined values for quality respectively signal strengthdefines values for controlling rxqual and rxlev in the regulation process. The

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variables, rxqual and rxlev are filtered with nonlinear exponential filters inorder to eliminate variations of temporal nature. The measurement reportingcauses a delay that typically is three periods.

The controlling parameter for rxqual in the regulation is qdes, and forrxlev the parameter ssdes. The qdes value is the target value that specifiesthe desired quality. Internally, qdes and rxqual are converted to C/I-valus,expressed in dB according to Table 3.1. Linear interpolation is used to realizeC/I.

Table 3.1: The conversion between qdes, rxqual and C/I. The unit dtqustands for deci-transformed quality units.

qdes [dtqu] 0 10 20 30 40 50 60 70

rxqual 0 1 2 3 4 5 6 7

C/I [dB] 23 19 17 15 13 11 8 4

The instruction for the change in power for the regulation is given by

pu = α ⋆ (ssdes − rxlevfiltered) + β ⋆ (qdesDB − rxqualDBfiltered) (3.1)

where α and β is the path loss respective quality compensation and qdesDBand rxqualDBfiltered are the qdes and rxqual mapped to C/I as in table 3.1[6]. The power level down regulation order is then given by

PL = INT (−pu

2) (3.2)

where INT truncates the power level to a higher value. PL could have valuesfrom 0 to 15, and that represent a down regulation of 0 to 30 dB, which couldbe seen in the final output power level by the BTS,

BTS output power = pmax − 2 ∗ PL (3.3)

where pmax correspond to full power.The existing power control algorithm accepts lower quality in single con-

nections if the whole system experiences a gain in quality. It considers thesystem quality and not the quality for single mobiles as the main regulatefactor. If a mobile experience lower signal quality than the target value,the transmitted power to that mobile will be increased. However, it willonly increase the power so that the signal quality changes towards the tar-get value and not actually achieve the target value. This regulation is toprevent “party effect”. The party effect can be describes as, if one mobileexperience low signal quality, the transmitted signal power will be increasedto that mobile. This results with an increment of the interference at other

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mobiles. These mobiles then require higher signal power and the interferenceat the first mobile is increased. Finally all mobiles will be transmitting withmaximum power, and this effect it is called the party effect. The existingpower control algorithm prevents this by just regulating towards the targetvalue. This is done by setting β < 1 in equation 3.1 [6].

To get a good understanding in the power regulation, knowledge abouthow much the output power will be down regulated for certain signal strengthor quality is necessary. Hence, the dependence between, signal strength,quality and down regulation is important. A way of studying these quantitiesis in a plot describing the behavior of the algorithm. This could be seen inFigure 3.2. How great the down regulation is, depends on the values ofrxqual and rxlev.

Figure 3.2: Principle for down regulation. The values rxlev and rxqual arethe measured values before any exponential filtering.

In the figure above it is shown how the power is down regulated. Thecontrolling values for the desired signal strength and quality, ssdes and qdes,are set to define the point where the two separate planes of the algorithmmeet, point marked 1 in Figure 3.2, and the positions of the planes, marked2 and 3 in Figure 3.2. Point 1 is at approximately rxqual = 3, which is equal

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to qdes = 30, and rxlev = 14. Plane 2 regulates mainly against the signalstrength to avoid lower power than the noise floor and plane 3 regulatesmainly towards quality.

3.3 EMR

The EMR (Enhanced Measurement Report) is a standardized measurementreport that contains additional information compared to the earlier mea-surement report. Like the old measurement report it contains informationof the performance of the transmission, for example rxlev and rxqual. Theadditional information in the EMR are the mean and the CV (coefficientof variation) of the bit error probability (BEP). These values are calledMEAN_BEP and CV_BEP, and they are calculated as an average overthe frames in a measurement period. The CV_BEP has a general definitionas the standard deviations divided by the mean value.

3.4 Problem statement

The existing power control algorithm adjusts the transmitting powers totrack a predefined quality value, to keep the system quality at an acceptablelevel. A fixed value of target BER, qdes, is used as the predefined value forquality control. However, there are some problems with using qdes as thepredefined quality value. First, BER might not be a good measurement forquality, which implies that quality might change but BER does not. Theother problem is the usage of a fixed target value for all different situations.This means that a pre-study to determine the proper fixed value need to bedone, and the value could not be changed in an ongoing system.

However, the main problem with the existing power control algorithmis the amount of parameters that needs to be predefined. Reducing theseparameters makes the algorithm less complex and more intuitive.

A method that automatically sets and adjusts this fixed target valueif the environment or other factors changes is desirable. This would be away to avoid predefining a number of parameters and thus make the powercontrol more intuitive. The problem with setting the value initially will alsobe solved due to the automatic tracking.

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Chapter 4

Simulator description

In this chapter the simulation model is described, for example how the simu-lation environment looks like and how some functions works. The simulatorhas been developed at Ericsson Research and is named FHRUNE and it hasbeen used in all simulations.

4.1 Simulation model

The simulation model is based on the real GSM system network. The modelcontains an environment that takes things like propagation and thermal noiseinto account. The model also gives opportunity to set parameters that con-trol how the GSM system should work. In this work, the possibility to adjustthe parameters in the power control algorithm is of special interest. This im-plies that there are possibilities to adjust parameters to change the behaviorof the system. Like the real GSM system the simulation model also uses ameasurement report to extract data from the environment.

FHRUNE uses three different time interval levels because updating allparameters at the shortest time interval would be both unnecessary and in-efficient. Parameters like power and mobile positions change only at definedmeasurement period intervals, 480 ms in GSM. The longest time interval istherefore represented by the measurement period. The next time intervalrepresents the length of a speech frame or a block, which contains 20 ms ofinformation. Each measurement period has 26 blocks. 24 blocks is used tocarry the information and signaling and empty bursts constitute together thetwo extra blocks. The shortest time interval is for the parameters changingfastest and is the burst level.

A schematic view of the main function in FHRUNE is shown in Figure4.1. Before entering the main loop all variables and system parameters aredeclared and initiated. In the main loop new mobiles are created and addedto the system. They are given an initial position and speed within the cellplan. Path loss between all base stations and all mobiles are calculated

14

and allocation for new mobiles or hand-over for already existing mobilesare also taken care of in the beginning of the main loop. Finally, beforeentering the inner loop a number of parameters for both mobiles and basestations are updated, for example the transmit powers. In the inner loopsome packet scheduling are done and then on burst level implemented bymatrix operations the C/I values for all mobiles are calculated. The C/Ivalues are used to estimate the quality for both speech and data users. Whenthe inner loop is finished data is extracted and logged. Finally in the mainloop, users with low speech quality are removed together with completedcalls and all remaining mobiles are given a new position and speed.

Measurementperiod

Frameperiod

Initiation

Create trafficPath loss calculationsAllocation and blockingInitiate and update user specific data

Packet scheduling

Calculate C/I and quality(Burst level)

Extract and log dataComplete and drop callsMove mobiles

Figure 4.1: Schematic view of the FHRUNE simulator.

15

4.2 Basic functionality

The functions in the real GSM system are modeled by the system simula-tor FHRUNE. Some of the basic functionalities are described below. Thesimulator must both simulate the environment and the GSM system. Thepropagation model and the fast fading are typical parts used to model theenvironment. Frequency hopping, discontinuous transmission (DTX) andpower control are all functions in the GSM system and strives to improvethe system performance.

4.2.1 Propagation model

Once for each measurement period a G-matrix is calculated. The G-matrixhas a row for each mobile station and a column for each base station. Avalue in the matrix includes path loss, antenna gain and slow fading andeach value represents a mobile/base station pair. The matrix updates oncea measurement period. The innermost level inside the inner loop calculatesdifferent fast fading values for each burst and add them to the G-matrix.This means that for each step of the inner loop four updated matrices aregenerated. The values in the G-matrices are used to calculate the resultingC/I at the receivers in the system for each measurement period. The up- anddownlink calculations are performed separately and hence there are differentmatrices for each direction.

4.2.2 Fast fading

The fast fading is caused by multiple reflections close to the receiver pro-ducing a Rayleigh distributed fading pattern. The fading values can varyconsiderable because of the dependence of both the used frequency and theposition of the receiver.

In the simulator a Rayleigh fading map models the fast fading. The rowsof this matrix represent the available carrier frequencies and each columnrepresents a distance of the Rayleigh fading path. The fading pattern of theRayleigh path is defined by the used frequency and the coherence bandwidth.The frequency used for each burst defines which row to use. Different mapswill be used for different values of the coherence bandwidths. The maps arepre-generated, because of the complexity of the Rayleigh fading model, anda parameter defines which map to use.

In FHRUNE, a fading path that represents a distance of 50 meters withseparate values at each millimeter is used. The length 50 meters is chosen toavoid correlation with distant values. Due to the separate frequency bandsfor up- and downlink in GSM, two separate maps for each value of thecoherence bandwidth, are used in parallel.

16

4.2.3 Frequency hopping

Frequency hopping is an important option in GSM systems by which networkperformance can be enhanced. Consider co-channel interference betweendifferent connections. Not all of the slots are in use on all of the physicalchannels on each site where they are reused. If we can take each caller ona particular sector and jump them from frequency to frequency, then eachuser runs a far lower risk of suffering from co-channel interference. This isbecause the co-channel interference is shared by many users.

The simulator gives a possibility to choose between GSM pseudo-randomsequences or ideal sequences from the MATLAB random number generator.In Figure 4.2 an example of frequency hopping sequences for some calls andsome bursts during a measurement period is shown. In the figure, GSMpseudo-random sequences are used. For example, call 1 is transmitting onchannel 7 in the first burst, but changes to transmit on channel 3 in thesecond burst. This hopping between which carrier frequency to transmit oncontinues throughout the call.

Channel numbers

bursts (104 columns)

1

2

3

4

5

6

7 3 7

6 2 8

1 5 3

call

. . .

. .

.

. .

. .

. .

.

Figure 4.2: Format of the frequency hopping matrix.

4.2.4 Discontinuous transmission

Discontinuous transmission (DTX) means that the base station instructsthe mobile station to shut down the transmission during the silent periodsin a conversation. This is done to avoid unnecessary transmission and saveenergy. The most important part in DTX is the voice detection, which hasto separate the voice from the background sounds.

The DTX is modeled in the simulator on speech frame level as a twostate machine, active respectively inactive. The switching between states iscontrolled by parameters that indicate whether the state is active or inactive.

17

4.2.5 Quality estimation

The C/I-values that is calculated in the inner loop for each burst is onekind of quality measurement used in FHRUNE. The C/I-values describesthe relationship between the signal carrier power and the interference power.However, the simulation model is designed to have a number of differentquality measurements available. In the sections below some definitions ofquality measurements used in this work are presented.

A better quality measure than the C/I-values is one that is based ona method that maps the C/I-values to frame error probabilities for speech.The C/I-values are used as input to a process that decides if each frameis successfully received or not. These mappings are the result of link levelsimulations and the process could be seen in Figure 4.3 and is describedbelow.

table lookup

group and calculate

two−dim. table lookup

random process

FER

C/I

BER

µ , σ

FEP

Figure 4.3: The steps in the mapping from C/I to FER.

In the first step of the process all the C/I-values are mapped to bit er-ror probabilities for each burst, in other words each individual C/I-valuecorrespond to an individual bit error probability. The mapping is imple-mented as a one-dimensional lookup table. The bit error probability valuesare grouped in speech frames, and the mean µ, and the standard deviationσ, are calculated for each frame as

µ =1

n

n∑

i

BEPi, (4.1)

18

σ =

√

√

√

√

1

n − 1

n∑

i

(BEPi − µ)2. (4.2)

The values BEPi are the bit error probabilities for each burst. The cal-culations are done per frame and since each frame consists of eight bursts,n is equal to 8. The mean and standard deviation are then used in thetwo-dimensional lookup table, Figure 4.4, to get FEP. One value of errorprobability is extracted from each pair of mean and standard deviation. [7]

00.1

0.20.3

0.40.5

0

0.1

0.2

0.3

0.4

0.50

0.2

0.4

0.6

0.8

1

mean

The lookup table as a figure

std

FE

P

Figure 4.4: The lookup table for mapping mean and standard deviation toFEP shown as a figure.

The FEP values are used in a random process to decide if each frameis erroneous or not. In the random process a uniformly distributed randomvector is compared to the FEP according to

frameerror = random(size(fep)) < fep, (4.3)

where frameerror is a vector containing ones and zeros where a one indicatesa frame error, random(size(fep)) is a uniformly distributed random vectorand fep is the frame error probability. The frame error is used to calculatethe frame erasure rate (FER).

19

Chapter 5

Tested algorithms

The proposed method for dynamically regulating qdes is by adding an outerloop to the existing power control. The implementation of the outer loopin the simulator is included as a function in the main part of the existingsimulator FHRUNE. The outer loop has the purpose to calculate a qdes valuebased on some information for the controlling of the inner loop. This targetvalue could be extracted in different ways. The following sections describethe method in general as well as three different approaches, using differentinformation, to calculate qdes. This chapter also presents the result from thesimulations of the three different approaches and an analysis of the result.Comparison with the theories is included to verify the results. Results fromboth unsuccessfully and successfully algorithms are presented.

5.1 General

The motivation for including an outer loop to the existing power controlalgorithm is that bit error rate (BER) is not necessarily well correlated toquality. BER is the measurement used in the current power control to cal-culate rxqual. Instead, for example the percentages of lost frames are morerelevant, since the effect of modulation, coding and interleaving is included.The information that should be used, and how it should be used, dependson the design of the outer loop. One possibility is the frame erasure rate(FER). However, the objective with the outer loop is to assign a qdes valuefor the existing power control algorithm to track. In Figure 5.1 the blockscheme over the existing power control in GSM is extended with a block forthe outer loop. The existing power control could be seen as an inner loop.The outer loop may use information from the EMR or other measurementsto produce a qdes value for the inner loop to track.

20

EnvironmentPowerqdesTarget

Algorithm

Current PCalgorithm

informationAdditional

Outer loop

Measurement report

RxQualInnerloop

Figure 5.1: The existing power control in GSM extended with the outer loop.

The purpose of the outer loop is to serve the inner loop with a dynamicqdes value that changes automatically. The measurement report should givethe outer loop additional information about the current quality in the system.The mean and the standard deviation of the bit error rate is additionalinformation in the enhanced measurement report and the outer loop mayuse these measurements to adjust the qdes value. A couple of differentapproaches of how to use the information are tested in this work. Algorithmsare set up, simulated and evaluated.

5.2 Parameter settings

Some of the parameters that describe the environment and also have animportant part in how to set the power control parameters are presented inTable 5.1. These parameters were held constant throughout all simulations.

21

Table 5.1: Fixed parameters that is used in the simulations.

Name Value Description

Frequency band [MHz] 900 Could be 900 or 1800.

Number of frequencies 27 Number of 200 kHz bands.

Frequency groups 3 The reuse factor.

Sectors per site 3 Could be 1 or 3.

Cell radius [m] 500 Size of each cell.

Number of time slots 1 One instead of 8 for simplicity.

Simulator time step [s] 0.48 Length of measurement period in GSM.

5.3 Outer loop based on EMR

This method uses the additional information from the EMR as the input tothe algorithm in the outer loop. The MEAN_BEP and CV_BEP are in thesimulator calculated for each frame. In this model they are calculated as theaverage value over a measurement period, in other words as an average of 24values.

EnvironmentPowerqdesTarget Current PC

algorithm

CV_BEPMEAN_BEP

Algorithm

EMRRxQual

Figure 5.2: Block scheme for the existing power control algorithm extendedwith an outer loop based on EMR.

5.3.1 Outer loop based on frame erasure rate

This method is based on the frame erasure rate (FER). FER is defined asthe percentage of erroneous frames. A target value, FER_target, is used asthe input value. In this method the target value is 0.8%. Basically, the qdesvalue is increased when FER is smaller than FER_target and decreasedwhen FER is greater than FER_target. The idea in this method is that

22

a specific qdes value is used for each specific mobile. Hence, qdes could bedifferent for each mobile depending on the quality of each connection. Theouter loop strives to increase quality in each specific mobile. In Figure 5.3the blocks in the outer loop with the proper input values are displayed.

FER

Comparison

measurement

Extractingquality

CV_BEPMEAN_BEP

qdesold

changeqdes qdesFER_target

FER_filtered

Filtering

Figure 5.3: The outer loop when the control algorithm is based on FER.

The input values to the outer loop are partly estimated from the EMRand partly defined by a user as a fixed value. From the measurement reportinformation to define the FER is used, as described in section 4.2.5 above.The MEAN_BEP and the CV_BEP could be converted to the mean andstd in Figure 4.4 and hence be used to extract FER in the simulator. Themean is equal to MEAN_BEP, and the std is calculated as,

σ = CV _BEP ∗ µ (5.1)

where σ and µ are the mean and the std. However, in the simulator a valueof FER calculated for each frame is used.

FER is than used to calculate a value that is compared to the fixed targetFER value, FER_target = 0.8%, defined by the user. The fixed target FERcorresponds to the percentage of useless frames that could be accepted. Anexponential filtering will be done on the FER for each single mobile,

FER_filteredn = α ∗ FER + (1 − α) ∗ FER_filteredn−1. (5.2)

where α = 0.5. This result is then compared to the FER_target to get thedifference and then multiplied with a constant C to get the difference in theproper unit. The conversion constant is also used to minimize the effect ofquick changes in FER and will also decrease the change in qdes. Finally, thechange is added to the old qdes values,

23

qdes = qdesold + qdeschange, (5.3)

where qdeschange is defined as

qdeschange = C ∗ (FER_filtered − FER_target). (5.4)

This algorithm should slowly adjust the values of qdes, for each mobile tohopefully strive against a FER lower than target FER.

The results from the simulations of this algorithm show no improvementof the system. This could be described by the fact that the outer loop has toomuch influence and disturbs the existing power control algorithm. Basically,the outer loop takes away the handling if the party effect. This is becausethe outer loop contradicts to the inner loop and will change qdes until thedesired FER is achieved. The FER value could be seen as a measure ofquality and when FER is high for a single mobile the outer loop strives tolower the FER by regulate the qdes value for that specific mobile. The goalis no longer to increase the whole system quality but just single mobiles.

Figure 5.4 shows the amount of satisfied users at different traffic loadsfor system with or without an outer loop. The number of satisfied users isdefined as the amount of mobiles with the average FER, during the lifetimeof a connection, lower than one percent. The equation is

satisfied users =1

M

M∑

i=1

FERi < 1%, (5.5)

where M is the total number of mobiles and FER is the frame erasure ratefor each mobile. This definition of the number of satisfied users are just oneof many.

24

0 5 10 1575

80

85

90

95

100FER_target = 0.8%, alpha = 0.5

Sat

isfie

d us

ers

[%] (

FE

R <

1%

)

Traffic load [Average users per cell]

PC without OLPC with OLno PC

Figure 5.4: Satisfied users at different traffic loads.

In the figure above it is obvious that there are more satisfied users whenthe system uses a power control algorithm without an outer loop based onFER. Although, the performance is better with the outer loop compared towhen no power control is used. This means that the effect of the powercontrol algorithm is decreased when this outer loop is included.

5.3.2 Outer loop based on coefficient of variation

This method is based only on the changes of CV_BEP. Removing the de-pendence of the MEAN_BEP, removes the ignorance of the party effect, aswas presence in the outer loop based on FER. The benefit is that the outerand the inner loop no longer contradicts each other. The idea is that thevalues of CV_BEP are directly mapped into qdes values. More precisely,the equivalent values of CV_BEP at the desired target FER level curve willbe found and depending on the position, the qdes is set to an appropriatevalue. The qdes value is thus not totally dynamic, thou it changes betweenfixed values depending on the value of CV_BEP. Although, the changes inqdes are automatic. The fixed changes are performed on mobile level, inother words each mobile have specific qdes.

The interesting part in Figure 4.4 for the lookup table is that for higher

25

values of the standard deviation it is possible to have a higher value of themean and still maintain at an acceptable FER level. For a specific targetFER, FER_target = 1%, a desired level curve could be extracted. In Figure5.5, a plot over how the coefficient of variation of BER varies in relation toBER is shown. CV of BER and BER is directly mapped from the bit valuesCV_BEP and MEAN_BEP. In the figure there is also an example of howan approximated desired target FER level curve could look like.

0 0.05 0.1 0.15 0.2 0.250

0.5

1

1.5

2

2.5

3

3.5

4All mobiles at all times during 30 sec

BER [%]

Coe

ffici

ent o

f var

iatio

n of

BE

R

FER=1%

Figure 5.5: BER and CV of BER is plotted against each other. Every dotgives the BER and CV of BER for each mobile at each measurement time.An approximation of a level curve for FER_target = 1% is also in thefigure.

If there is possible to find all the equivalent values of CV of BER at BERfor the interesting part of the desired target FER level curve, it could be usedto create a function f(CV _BEP ) that is independent of MEAN_BEP andhence the only depending variable is CV_BEP. The function f(CV _BEP )and the desired target FER level curve is then used as a mapping functionthat indirectly maps the CV_BEP to new qdes values. Basically, a highervalue of CV_BEP means that qdes should have a higher value. How bigchange depends on the FER level curve. It is possible to map to qdes becauseBER could be converted to qdes.

26

The task is to examine whether the mobiles have CV_BEP that is higheror lower than the average and change the qdes value according to that.However, there are some problems. First, it is very hard to create a functionf(CV _BEP ) that is independent of MEAN_BEP, in other words there arehard to find all the equivalent values for the CV_BEP. Even if it would bepossible the CV_BEP for a single mobile varies too much from one time toanother. In other words at one time CV_BEP is higher than the averageand next time lower. In Figure 5.6 a plot over how CV of BER varies aroundthe average line for one mobile. The dots represent the values in the firstmeasurement period, the second measurement period and so on. This figureshows that a control in this way is nearly impossible. Even if it could bepossible for some mobiles to say that CV of BER is high or low, the changein qdes is very small. This is because the target FER level curve only givessmall changes in BER for a change in CV of BER.

0 0.05 0.1 0.15 0.2 0.250

0.5

1

1.5

2

2.5

3

3.5

4The average line and values for one single mobile during a call

BER [%]

Coe

ffici

ent o

f var

iatio

n of

BE

R

1

2 4

13 14

9

8

11 12

7

3

6 10

5 Average line

Figure 5.6: A plot over how CV_BEP changes around the average line forone single mobile during a call. The call lasts for nearly 7 seconds and it isimpossible to see a trend for the CV_BEP values.

27

5.3.3 Summary

None of the methods where the outer loop is based on EMR shows anyimprovment to the total system. Using FER and controlling qdes for everysingle mobile contradicts the existing power control by not considering theparty effect. This implies that the algorithm no longer strives for maximumsystem quality.

Removing MEAN_BEP and only using CV_BEP as the input to theouter loop removes the possibilities for the same drawbacks as in the previousmethod. However, this method is hard to realize, very unstable and if itwould work only give small changes in qdes.

The methods for the outer loop using EMR as input are left behind andother solutions for input measurements are considered.

5.4 Outer loop based on power distribution

This method is based on the idea that it is preferable in a system thatas many connections as possible are actually using power control, in otherwords are not limited by the availible power range. It is also assumed thatthis number can be controlled by the parameter qdes. This method controlsone qdes for the entire system.

5.4.1 Power distribution analysis

The transmitted powers in both uplink and downlink between mobile stationsand base stations are limited with a maximum and a minimum effect. Fromthe maximum effect pmax there are steps of 2 dBm down to the minimumeffect pmin. The maximum and minimum powers are pmin = 16 dBm, pmax =30 dBm. The transmitted power are described in equation 3.3 in section 3.2.

If link quality is low, transmitted powers with higher effect are used andlower effects are used when link quality is high. However, a simple methodthat estimates the amount of users not limited by the power range could bedescribed as,

regulating fraction =number of pbetween max and min

total number of p. (5.6)

In equation 5.6 regulating fraction is defined as the number of userstransmitting with power level between the minimum and maximum value,divided with the total amount of transmitted powers. Only looking at theregulating fraction does not give any information about how to change qdes.Another estimate that takes this into consideration is the difference betweenthe number of users transmitting with maximum respectively minimum ef-fects,

28

PCdiff =number of pmax − number of pmin

total number of p. (5.7)

This value will be positive if many mobiles are transmitting with high powerand negative if many mobiles are transmitting with low power.

The idea is that if a high number of mobiles transmit with a power inbetween the minimum and maximum value, then good system quality shouldbe achieved because there is high usage of power control. This holds onlyif high usage of power control implies good system quality, in other wordsif usage of power control correlates with the number of satisfied users. Toexamine this some simulations on the existing system with fixed qdes hasbeen done.

In Figure 5.7, the power distribution are displayed in histograms. Thehistograms are from two different occasions, one with a relatively low trafficload and the other with a relatively high traffic load. As we see in the figure,for the same qdes, when there are higher traffic load, a lot of mobiles aretransmitting on maximum effect. If the method could regulate the algorithmto decrease the powers for some of those mobiles a higher regulating fractionwould be accomplished. This is the idea of how this method should work.

29

16 18 20 22 24 26 28 300

5

10

15

20

25

30

Low load

Power [dBm]

Num

ber

of u

sers

[%]

16 18 20 22 24 26 28 300

5

10

15

20

25

30

High load

Power [dBm]

Num

ber

of u

sers

[%]

Figure 5.7: Histograms for two different occasions. In the left plot the systemhas experienced a relatively low traffic load and in the right a relatively hightraffic load.

The correlation between the regulating fraction and the number of satis-fied users gives a hint of whether there is a relation between the transmittedpower distribution and quality. As mentioned before, regulating fraction isdefined as the amount of powers that is not transmitting on minimum ormaximum effect. The number of satisfied users is defined as the amount ofmobiles with the average FER, during the lifetime of a connection, lowerthan one percent, as defined in section 5.3.1.

In Figure 5.8 the amount of satisfied users are plotted against qdes fora specific traffic load. The figure below shows how the amount of satisfiedusers changes by an adjustment of qdes. This plot is for a situation with fixedenvironment conditions. The qdes value that implies the highest amount ofsatisfied users may however, vary with the environment conditions.

30

0 10 20 30 40 50 60 7070

75

80

85

90

95

100

qdes

Num

ber

of s

atis

fied

user

s [%

]Satisfied users for different qdes

Figure 5.8: Number of satisfied users for a specific condition for differentqdes.

The correlation between the regulating fraction and the number of sat-isfied users gives a hint of whether this method could be useful or not. .In Figure 5.9 these two parameters are plotted against qdes for a fixed lowtraffic load.

31

0 10 20 30 40 50 60 7070

75

80

85

90

95Amount of users for different qdes, low load

qdes

Sat

isfie

d us

ers

[%]

0 10 20 30 40 50 60 700

50

100

Reg

ulat

ing

frac

tion

[%]

Satisfied usersRegulating fraction

Figure 5.9: The usage of power control and the amount of satisfied usersplotted for different qdes. The traffic load is fixed and low.

The figure above shows that the maximum value for the both lines ap-pear at approximately the same value of qdes, and the curves have similarappearence. This high correlation indicates a relation between the regulatingfraction of the transmitted powers and the number of satisfied users. Thismeans that information of the power distribution could be used to increasethe amount of satisfied users. If the system strives to find the value of qdesthat gives the highest regulating fraction, this will also imply that the sys-tem achieves the highest number of satisfied users. The same situation asabove is plotted in Figure 5.10, but with a higher load. In this plot the bothmaximum values appear approximately at the same value of qdes. Obviousfrom these two figures is that an increase in traffic load decreases both thenumber of satisfied users and the regulating fraction.

32

0 10 20 30 40 50 60 7070

75

80

85

90

95Amount of users for different qdes, medium load

qdes

Sat

isfie

d us

ers

[%]

0 10 20 30 40 50 60 700

50

100

Reg

ulat

ing

frac

tion

[%]

Satisfied usersRegulating fraction

Figure 5.10: The plot shows the regulating fraction of the transmitted powersand the number of satisfied users for a high traffic load.

The same situation as above is plotted in Figure 5.11, but with a evenhigher traffic load. In this plot the both maximum values do not appear atthe same value of qdes. However, the results points to a relation betweenthe number of satisfied users and the regulating fraction of the transmittedpowers.

33

0 10 20 30 40 50 60 7070

75

80

85

90

95Amount of users for different qdes, high load

qdes

Sat

isfie

d us

ers

[%]

0 10 20 30 40 50 60 700

50

100

Reg

ulat

ing

frac

tion

[%]

Satisfied usersRegulating fraction

Figure 5.11: The plot shows the regulating fraction of the transmitted powersand the number of satisfied users for a high traffic load.

Figure 5.12 below shows plots of the difference, PCdiff , for some differ-ent traffic loads. A high value, in other words a high difference, means thatmany mobiles transmit with maximum effect, which imply that a change inqdes is desirable. Achieving the value zero correspond to finding the optimalvalue of qdes for this situation.

34

0 10 20 30 40 50 60 70−40

−20

0

20

40

60

80

100Difference between no. of max and no. of min powers

qdes

PC

diff

[%]

Low loadMedium loadHigh load

Figure 5.12: The difference between number of mobiles transmitting on max-imum effect and the number of mobiles transmitting on minimum effect forsome different traffic loads.

From the figure above it is visible that the lines for the different trafficload are almost linear and have the same slopes. Assuming that they infact are linear with the same slope means that it is simple to adjust qdesaccording to the difference. A change in PCdiff implies a change in qdes. Ifthe optimal values for the difference is zero this plots could be compared tothe plots showing the regulating fraction in Figure 5.9 to 5.11. The maximumvalues of the regulating fraction appears at higher values when the trafficload is increased. The same behaviour could be seen in Figure 5.12. Wherethe lines crosses zero appears not exactly at the same qdes as where theregulating fraction has the maximum value, for the same traffic load.

5.4.2 Simulated algorithm

This method is based on statistics of all mobiles for a measurement period.In this simulations the environment is similar for each cell and the powerdistributions is therefore for all cells in the entire system. The qdes valuecontrolled by the outer loop is in this method common for all mobiles. Away to find out how to change the target value is to look at the difference

35

between the number of mobiles transmitting with the maximum respectivelyminimum power, PCdiff . The block scheme for this method is shown inFigure 5.13.

qdesold

qdeschangeqdesC

PCdiff_average

Averaging

PCdiff

Extractingmeasurement

Power distribution

Figure 5.13: A block scheme of the outer loop based on the usage of powercontrol.

The value PCdiff is calculated from the power distribution as describedin equation 5.7. In the algorithm block, the first step is an avering of thepresent value and the exponential filtered previous values. This differencein power usage is than converted to a change in qdes and added to the oldvalue, qdesold, to create the new qdes,

qdes = qdesold + C ∗ PCdiff_average, (5.8)

where PCdiff_average is calculated from PCdiff ,

PCdiff_average =1

OLtime

OLtime∑

i=1

PCdiffi ∗ e(−(OLtime−i)). (5.9)

This model performed a possible increment in quality for the system.The main idea with this method is to adjust the qdes value automatically asthe environment changes. The target value is the same for the entire systemand is depending on the system quality. The equation 5.9 is not optimal andan improvement might also improve the performance of the algorithm. InFigure 5.14 a plot that shows how the algorithm works is displayed. This plotis an example of the initial adjusting of qdes. It is clear how the algorithmstrives to find a qdes that is optimal for this specific situation. When theenvironment condition changes the algorithm will find the new qdes. Thecontrol of qdes is based on PCdiff , showed in Figure 5.12, and strives toa PCdiff equals to zero. The power control algorithm without this outer

36

loop uses a fixed qdes value, which obviously is not the optimal value mostof the times.

0 20 40 60 80 100 120 140 160 1800

10

20

30

40

50

60

70The first adjusting of qdes, medium load

time [s]

qdes

Figure 5.14: The qdes value is adjusted to a proper value, depending on thecurrent environment in the cell.

The performance of this algorithm is not fully evaluated. However, inFigure 5.15 a plot over satisfied users compared to power control with a fixedqdes is presented. The result in the plot shows that the performance is ap-proximately equal with or without an outer loop. However, this simulation isdone for an optimal value of qdes, which means that the power control witha fixed qdes will be the currently best solution. In real systems, variations infor example traffic load and radio transmission condition in each cell is com-mon, which means that an optimal value of qdes is hard to find. This meanthat the power control algorithm might have to use this method to retainthis high system performance. This because the outer loop algorithm adjustqdes to strive for a high system performance when environment changes.

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0 5 10 1575

80

85

90

95

100

Traffic load [Average users per cell]

Am

ount

of s

atis

fied

user

s [%

]Number of frequencies = 27, qdesinit = 45

no PCPC without OLPC with OL

Figure 5.15: The number of satisfied users with and without an outer loopin the power control. The result with no power control is also displayed.

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Chapter 6

Discussion

This chapter contains the conclusions of this work. A part will also proposesome ideas for future work.

6.1 Conclusions

It has been shown in this work that the power control algorithm extendedwith an outer loop is a potential method to increase the performance of thepower control and increase the system performance. However, the outer loopperformance is depending on which parameters used for input measurementsand how they are used.

Using frame erasure rate (FER) as the quality measurement and adjust-ing a specific qdes for every connection implies some problems. The mainproblem, in this case, is that the entire control algorithm strives to get thesame quality for each mobile, which does not imply maximum system quality.Instead, the algorithm is shown to have effects that eliminate the essentialprinciple of power backoff to avoid the so called party effect, and is thereforenot recommended. It has also been shown that the coefficient of variation ofthe bit error probability (CV_BEP) has a little effect on how qdes shouldbe adjusted.

The most promising algorithm in this work is the one using the powerdistribution as the input parameter to the outer loop. It is shown that thereis high correlation between the number of satisfied users and the number ofusers within the regulating window, i.e. the number of users not limited bythe maximum or minimum power levels. The final proposed algorithm hasthe difference between maximum and minimum transmitted powers as thecontrolling parameter. The result is an algorithm that changes qdes as thetraffic load changes.

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6.2 Further studies

• The power distribution algorithm is in this work implemented and eval-uated using information from the entire system. It would be intrestingto use information from each cell instead.

• The algorithm should be tested for mixed services, e.g. AMR FR/HR.

• This algorithm only considers interference. For powers around thenoise limit, regulating according to rxqual could be useful.

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Bibliography

[1] L.Ahlin, J.Zander. ’Digital radiokommunikation - system och metoder’.Studentlitteratur, Lund, Sweden, 1992.

[2] T.Rappaport. ’Wireless Communication - principles and practicer’. Sec-ond edition. Prentice Hall, New Jersey, USA, 2002.

[3] F.Gunnarsson, F.Gustafsson, J.Blom. ’Estimation and outer loop powercontrol in cellular radio systems’. Linköping University, February, 2001.

[4] L.Ahlin, C.Frank, J.Zander. ’Mobil Radio Communication’. Studentlit-teratur, Lund, Sweden, 1995.

[5] J.Tisal. ’The GSM network - GPRS evolution: one step closer towardsUMTS’. Second edition. Wiley, Chichester, England, 2001.

[6] M.Almgren, H.Andersson, K.Wallstedt. ’Power control in a cellular sys-tem’. Stockholm, Sweden, 1994.

[7] Håkan Olofsson. “Improved Interface Between Link Level and SystemLevel Simulations Applied to GSM”. ICUPC ’97. 1997.

[8] 3rd Generation Partnership Project, Technical Specification, 45.008.2004.

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Appendix A

List of Abbreviations

3G 3rd GenerationBEP Bit Error ProbabilityBER Bit Error RateBSC Base Station ControllerBTS Base Tranceiver StationC/I Carrier to Interference rationCV Coefficient of VariationDTX Discontinous TransmissionEDGE Enhanced Data rates for GSM EvolutionEMR Enhanced Measurement ReportFEP Frame Error ProbabilityFER Frame Erasure RateFDMA Frequency Division Multiple AccessGMSC Gateway Mobile services Switching CenterGMSK Gaussian Minimum Shift KeyingGPRS Global Packet Radio ServicesGSM Global System for Mobile communicationISI Inter Symbol InterferenceMS Mobile StationMSC Mobile services Switching CenterPC Power ControlPSK Phase Shift KeyingPSTN Public Switched Telephone NetworkTDMS Time Division Multiple Access

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