Master-optimization of Egprs Link Adaptation

HELSINKI UNIVERSITY OF TECHNOLOGY Department of Electrical and Communications Engineering

Jussi Nervola

OPTIMIZATION OF EGPRS LINK

ADAPTATION

COMPANY CONFIDENTIAL VERSION

(Appendix D included)

Thesis submitted in partial fulfillment of the requirements for the degree of Master of

Science in Engineering in Espoo on 16.01.2007

Supervisor: Professor Riku Jäntti

Instructor: M.Sc. Petri Grönberg

Company Confidential Version

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HELSINKI UNIVERSITY OF TECHNOLOGY Abstract of Master’s Thesis

Author: Jussi Nervola Name of the Thesis: Optimization of EGPRS Link Adaptation Date: 16.01.2007 Number of pages: 76

Department: Department of Electrical and Communications Engineering Professorship: Communications Laboratory

Supervisor: Professor Riku Jäntti Instructor: M.Sc. Petri Grönberg

Abstract: EDGE (Enhanced Data Rates for GSM Evolution) with packet based service EGPRS (Enhanced GPRS) offers packet data service for the users of GSM network. EDGE was introduced in Release’99 version of GSM standard and it improves the performance of the system to a new level. Wireless networks are working in very challenging environment. The quality of a connection can change from very good (with line of sight to the base station) to very poor in short time. The performance of the system has to be optimized for every radio condition. In EGPRS there are nine different modulation and coding schemes (MCS) that offer different amount of robustness for data transfer. The coding scheme that offers the best performance in the current situation from the user point of view should be used. This requires automatic adaptation to the different circumstances from the system. The automatic selection of the most suitable coding scheme is called link adaptation. This thesis concentrates on optimizing link adaptation for EGPRS. The target was to get the performance of EGPRS link adaptation to the optimum level. First the baseline measurements were made and the performance and improvement potential of the current system were analyzed. Then changes to the link adaptation were implemented according to the analyses. Various versions of link adaptation algorithm were created and tested to see which offered the best performance and if the changes were working as intended. After every new version the gap between the implemented and ideal link adaptation was closing. As a result of this thesis the performance of EGPRS link adaptation was improved nearly to the ideal level in almost every environment. The performance improvement with the final optimized link adaptation version was clearly seen in laboratory and live network. In laboratory the throughput performance was improved by +11% in average. Coverage for EGPRS service was improved by 1-6 dB depending on circumstances. In live network throughput improvement in downlink data transfer was +11% and in uplink data transfer +31%. Although the results with the optimized link adaptation were optimal in almost every environment, there was still some room left for improvements with certain mobile stations (MSs).

Keywords: EGPRS, EDGE, link adaptation, EGPRS performance, packet data


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TEKNILLINEN KORKEAKOULU Diplomityön tiivistelmä

Tekijä: Jussi Nervola Työn nimi: EGPRS linkkiadaptaation optimointi Päivämäärä: 16.01.2007 Sivumäärä: 76

Osasto: Sähkö- ja tietoliikennetekniikan osasto Professuuri: Tietoliikennelaboratorio

Työn valvoja: Professori Riku Jäntti Työn ohjaaja: DI Petri Grönberg

Tiivistelmä: EDGE (Enhanced Data Rates for GSM Evolution) yhdessä pakettipohjaisen EGPRS (Enhanced GPRS)-palvelun kanssa tarjoaa pakettidatapalvelua GSM-verkon käyttäjille. EDGE esiteltiin GSM standardin versiossa Release’99, ja se nosti järjestelmän suorituskyvyn uudelle tasolle. Langattomat verkot toimivat eritäin haasteellisissa olosuhteissa. Yhteyden laatu voi vaihdella erinomaisesta erittäin huonoon lyhyessä ajassa. Järjestelmän suorituskyky on optimoitava jokaiseen radio-olosuhteeseen sopivaksi. EGPRS:ssä on yhdeksän eri modulaatio ja koodausluokkaa, jotka tarjoavat datansiirrolle eri määrän robustisuutta. Käytettävä koodaus tulee valita joka tilanteessa niin, että käyttäjän kokema suorituskyky maksimoidaan. Tämä vaatii järjestelmältä automaattista mukautumista ympäröiviin olosuhteisiin. Tätä automaattista koodauksen valintaa kutsutaan linkkiadaptaatioksi. Tämä diplomityö keskittyy EGPRS:n linkkiadaptaation toiminnan optimoimiseen. Työn tavoitteena oli saada EGPRS:n linkkiadaptaation suorituskyky optimitasolle. Aluksi nykyisen järjestelmän suorituskyky mitattiin ja analysoitiin, jotta parannuspotentiaali voitiin selvittää. Analyysien perusteella linkkiadaptaatioon tehtiin muutoksia. Linkkiadaptaatiosta tehtiin useita versioita, ja kaikki eri versiot testattiin, jotta nähtiin, mikä tarjosi parhaan suorituskyvyn ja olivatko järjestelmään tehdyt muutokset oikean suuntaisia. Jokaisen version jälkeen ero toteutetun ja ideaalisen linkkiadaptaation suorituskyvyssä pieneni. Diplomityön tuloksena EGPRS:n linkkiadaptaation suorituskyky parani lähelle ideaalitasoa melkein kaikissa olosuhteissa. Suorituskyvyn parantuminen oli selkeästi nähtävissä sekä laboratorio-olosuhteissa että oikeassa verkossa. Laboratoriossa datan siirtonopeus parantui keskimäärin +11%. EGPRS palvelun kantama parani tilanteesta riippuen 1-6 dB. Oikeassa verkossa parannus datan siirtonopeudessa oli downlinkissä +11% ja uplinkissä +31%. Vaikka optimoidun linkkiadaptaation suorituskyky oli lähellä optimitasoa melkein kaikissa olosuhteissa, jäi suoristuskykyyn parannettavaa joidenkin puhelinmallien (Mobile Station) kanssa.

Avainsanat: EGPRS, EDGE, linkkiadaptaatio, EGPRS:n suorituskyky, pakettidata


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Contents

Contents .............................................................................................................................. 3 Preface ................................................................................................................................ 4 Glossary .............................................................................................................................. 5 1. Introduction................................................................................................................ 7 2. Global System for Mobile Communications (GSM) ................................................. 9

2.1. Network Switching Subsystem (NSS)............................................................. 10 2.2. Base Station Subsystem (BSS) ........................................................................ 10 2.3. Network Management Subsystem (NMS)....................................................... 11

3. General Packet Radio Service (GPRS) .................................................................... 12 3.1. Network Architecture ...................................................................................... 12 3.2. Protocol Architecture....................................................................................... 13 3.3. Mobile Stations................................................................................................ 15 3.4. Mobility Management ..................................................................................... 16

4. Enhanced Data Rates for GSM Evolution (EDGE) ................................................. 18 4.1. Enhancements to GPRS................................................................................... 18

5. Performance of EGPRS............................................................................................ 21 6. EGPRS Link Adaptation .......................................................................................... 24

6.1. Operation of Link Adaptation.......................................................................... 24 6.2. Incremental Redundancy ................................................................................. 26 6.3. Bit Error Probability as Channel Quality Criterion ......................................... 27 6.4. Link Adaptation Algorithm ............................................................................. 29

7. Test Scenarios for EGPRS Link Adaptation Measurements.................................... 31 7.1. Laboratory Test Scenarios ............................................................................... 32 7.2. Laboratory Measurement Configurations........................................................ 32 7.3. Live Test Scenarios ......................................................................................... 36 7.4. Test Cases for Laboratory and Live Network.................................................. 37 7.5. Earlier Measurements on Link Adaptation...................................................... 39

8. Measurement Results and Optimization of Link Adaptation................................... 41 8.1. Baseline Measurement Results........................................................................ 41

8.1.1. Measurements in Variable RX-level Scenario........................................ 42 8.1.2. Measurements in Variable C/I Scenario ................................................. 44 8.1.3. Improvement Potential of the Current Link Adaptation ......................... 48

8.2. Optimization of Link Adaptation .................................................................... 48 8.3. Measurement Results with Optimized Values................................................. 51

8.3.1. Measurements in Variable RX-level Scenario........................................ 52 8.3.2. Measurements in Variable C/I Scenario ................................................. 55 8.3.3. Measurements in Fading Scenario .......................................................... 57 8.3.4. Measurements in Live Network.............................................................. 59

9. Results of the Optimization...................................................................................... 66 9.1. Performance in Laboratory Environment ........................................................ 66

9.1.1. Downlink Performance ........................................................................... 66 9.1.2. Uplink Performance................................................................................ 68

9.2. Performance in Live Network ......................................................................... 68 9.3. Further Study Items and Future Improvement Potential ................................. 69

10. Conclusions.......................................................................................................... 70 11. References............................................................................................................ 71


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Preface

This thesis work has been carried out at Nokia Networks in BSS System Verification

team in Espoo, Finland.

I would like to thank the supervisor of this thesis, Professor Riku Jäntti, for his comments

and advices, my instructor Petri Grönberg for his excellent guidance during the thesis

work and my superior Jarmo Nissilä and my original instructor Veli-Pekka Ketonen for

their support. I want to thank also all members of BSS System Verification and BSC

System Testing teams for their support especially on test network configuration tasks.

Helsinki, January 16th, 2007

Jussi Nervola


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Glossary

3GPP 3rd Generation Partnership Project

8-PSK 8-Phase Shift Keying

ARQ Automatic Repeat Request

AuC Authentication Centre

BEP Bit Error Probability

BLER Block Error Rate

BSC Base Station Controller

BSS Base Station Subsystem

BTS Base Transceiver Station

C Carrier (power)

C/I Carrier-to-Interference Ratio

CS Circuit Switched

CS-1/2/3/4 Coding Scheme (GPRS)

DL Downlink

ECSD Enhanced Circuit Switched Data

EDGE Enhanced Data Rates for GSM Evolution

EGPRS Enhanced General Packet Radio Service

EIR Equipment Identity Register

ETSI European Telecommunications Standards Institute

FDD Frequency Division Duplex

FDMA Frequency Division Multiple Access

FEC Forward Error Correction

FTP File Transfer Protocol

GGSN Gateway GPRS Support Node

GMSK Gaussian Minimum Shift Keying

GPRS General Packet Radio Service

GSM Global System for Mobile Communications

HLR Home Location Register

HSCSD High Speed Circuit Switched Data

HTTP Hypertext Transfer Protocol

I Interference (power)

IP Internet Protocol

IR Incremental Redundancy


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LA Link Adaptation

LLC Logical Link Control

MAC Medium Access Control

MCS Modulation and Coding Scheme (EDGE)

ME Mobile Equipment

MS Mobile Station

MSC Mobile Switching Center

NMS Network Management Subsystem

NSS Network Switching Subsystem

PCU Packet Control Unit

PDP Packet Data Protocol

PDU Packet Data Unit

PS Packet Switched

RA Routing Area

Rel4 GSM Release 4

Rel99 GSM Release 99

RF Radio Frequency

RFLO RF Local Oscillator

RLC Radio Link Control

RTT Round Trip Time

RX-level Received Power Level

SAIC Single-Antenna Interference Cancellation

SGSN Serving GPRS Support Node

SIM Subscriber Identity Module

TBF Temporary Block Flow

TC Transcoder

TCP Transmission Control Protocol

TDMA Time Division Multiple Access

TSL Timeslot

TU Typical Urban (Fading model)

TX Transmitter

UL Uplink

VLR Visitor Location Register


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1. Introduction

GSM (Global System for Mobile Communications) is the most popular mobile

telecommunication standard in the world. The standardization work for GSM was

finalized in 1990. The original GSM network was designed for circuit switched traffic,

mainly for voice. As the demand for wireless packet based services was increasing, GSM

standard was developed further. The packet data capability was introduced by GPRS

(General Packet Radio Service) in the Release’97 version of GSM standard. More

advanced service EDGE (Enhanced Data Rates for GSM Evolution) with packet based

service EGPRS (Enhanced GPRS) was introduced in the Release’99 version of GSM

standard and it improved the performance of the system to a new level.

Packet based wireless networks are operating in far more demanding and changing

environment than wired networks. They have to use complex and sophisticated methods

to compensate the changes in radio environment. The quality of a connection can change

from very good (with line of sight to the base station) to very poor. The performance of

the system has to be optimized for every radio condition. When the quality of the

connection is good, there’s no need for heavy error correction and the user level

performance can be kept as high as possible. On the other hand, when the link quality is

poor, the error correction is the only way to get the user data through the network. In

EGPRS there are nine different modulation and coding schemes that offer different

amount of robustness for data transfer. The coding scheme that offers the best

performance in the current situation from the user point of view should be used. This

requires automatic adaptation to different circumstances from the system. The automatic

selection of the most suitable coding scheme is called link adaptation (LA).

This thesis concentrates on optimizing link adaptation for EGPRS. (Term optimization is

not used in this thesis in its mathematical meaning but referring to improving the

performance of the system.) First the current performance level of the system has to be

measured to find out the improvement potential. After that the optimized solutions for

link adaptation have to be created and implemented. When a new link adaptation version

is ready for testing, the performance of that version has to be measured to see if changes

done to LA were improving the performance enough. After the measurements, if there is

still potential for improvement, a new version of link adaptation is to be created and

tested.


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The target of this thesis is to get the performance of EGPRS link adaptation to the ideal

level. That would create real benefits for the users of EGPRS as the quality of service

would be improved. As the measurements are done with real network elements and not

just in simulations, the improvements should be fully realizable also in commercial

operators’ networks.

Chapters 2 – 4 provide brief introduction to GSM, GPRS and EDGE networks. Special

attention is paid to the issues that have effect on the functionality of link adaptation.

Chapter 5 discusses the performance of EGPRS service. Operation of EGPRS link

adaptation is explained thoroughly in Chapter 6. Chapter 7 describes the used test

scenarios and test cases for link adaptation measurements. Link adaptation optimization

work and measurement results with original LA and optimized LA are presented in

Chapter 8. The summary of measurement results is presented in Chapter 9. Finally

Chapter 10 concludes the thesis.


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2. Global System for Mobile Communications (GSM)

In this chapter the circuit switched GSM network is described. In the next chapter we will

go through the requirements for packet based services. Although this thesis concentrates

on Enhanced Data Rates for GSM Evolution (EDGE), it’s sensible to go through the

basics of circuit switched GSM and packet switched data services in GSM (GPRS) as

EDGE uses mostly the same infrastructure.

Global System for Mobile Communications (GSM) is a second generation digital cellular

network standard. It uses Time Division Multiple Access (TDMA), Frequency Division

Multiple Access (FDMA) and Frequency Division Duplex (FDD) techniques in its radio

interface [1]. The first GSM specifications were completed by European

Telecommunications Standards Institute (ETSI) in 1990. These specifications introduced

circuit switched service to the GSM network.

Figure 1: GSM network architecture

GSM network consists of three subsystems: Network Switching Subsystem (NSS), Base

Station Subsystem (BSS), and Network Management Subsystem (NMS). Mobile Stations

(MS) are needed to be able to use network services. MS is a combination of terminal

BTS MS BSC

HLR

AuC

EIR

PSTN

Base Station Subsystem Network Switching

Subsystem

Air A-bis A-ter

BTS

MSC/VLR TC

A

Network Management Subsystem

Database

servers

Workstations


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equipment or in other words Mobile Equipment (ME) and Subscriber Identity Module

(SIM). SIM holds data needed for the subscriber to use the network. The interfaces

between all these subsystems are open and therefore it’s possible to use equipment of

different vendors in every subsystem. GSM network architecture with circuit switched

service is presented in Figure 1.

2.1. Network Switching Subsystem (NSS)

Network Switching Subsystem is responsible for call control, charging and mobility

management in GSM network. The most important component in NSS is Mobile

Switching Center (MSC). It controls and routes all calls in the network. MSC has usually

also an integrated Visitor Location Register (VLR) where it stores information about the

subscribers in its service area. VLR has only a temporary database for the current users in

the area. Home Location Register (HLR) is used for storing subscribers’ data and location

permanently. The security to the GSM network is provided by Authentication Centre

(AuC) and Equipment Identity Register (EIR). AuC handles authentication and key

management of subscribers and EIR is a database that contains a list of all valid mobile

equipment in the network. AuC and EIR are usually implemented as a part of HLR.

2.2. Base Station Subsystem (BSS)

Base Station Subsystem is responsible for radio path control in GSM. It has three

components: Base Station Controller (BSC), Base Transceiver Station (BTS) and

Transcoder (TC). BSC is the central network element of the BSS and it controls the radio

network. Main functions of BSC are connection establishment between the MS and the

NSS, mobility management, statistical raw data collection and signaling support for A-

and Air-interfaces. BTS is a network component that handles the Air-interface taking care

of Air-interface signaling, ciphering and speech processing.

The third component of BSS, Transcoder, is used to transcode speech to right format for

the Air-interface and fixed networks. In the Air-interface speech is compressed to 13

kbit/s bit rate (Full rate) (or 5,6 kbit/s bit rate (Half rate)) from 64 kbit/s bit rate used in

PSTN.


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2.3. Network Management Subsystem (NMS)

The purpose of the Network Management Subsystem is to monitor various functions and

elements in the network. NMS is usually implemented using databases and workstations

that are connected to the network elements. The NMS has three main functions: fault

management, configuration management and performance management. The purpose of

fault management is to ensure correct operation of the network and create alarms if

something is not working properly in the network. Configuration management is used to

control the current and possible new configurations of the network. The plan for new

network configuration can be done beforehand and then later the planned changes can be

implemented quickly and easily. Performance management is used to collect performance

data from network. With this data the operator is able to see if the network meets its

planned performance levels and if there are differences between different areas in

performance.


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3. General Packet Radio Service (GPRS)

Circuit switched GSM offered also data service but the maximum data rates with CS data

were not high: 14,4 kbit/s. Also the circuit switched nature of the service was far from

ideal for bursty traffic. These were the main reasons why the standardization work began

for General Packet Radio Service (GPRS). GPRS offers packet switched based data

service for the users of GSM networks. Packet based networks offer better bandwidth

usage than circuit switched networks especially when the traffic is bursty like e.g. in web

browsing or receiving e-mails. GPRS has been in GSM standards since Release 97. It was

originally standardized by ETSI but now the standardization work has been handed over

onto the 3GPP.

The basic idea of GPRS is that the capacity that is not momentarily used by voice traffic

can be given to packet data users [1]. This helps to increase the average usage of

otherwise non-used radio resources (see Figure 2). As the GPRS data has lower priority

than voice, the voice users get service whenever they want despite of GPRS usage. Some

cells or timeslots can be dedicated only for GPRS use and so the packet service can be

offered also when all voice channels are reserved.

Figure 2: GPRS increases average network usage

3.1. Network Architecture

GPRS requires some new network elements to GSM network: Serving GPRS Support

Node (SGSN) and Gateway GPRS Support Node (GGSN). SGSN takes care of the

conversion between IP protocols and BSS protocols. It’s connected between BSC and

GGSN. SGSN also routes data to right GGSN, performs authentication, data compression

Time of day

Load

Voice traffic

Unused capacity

Load

Voice traffic

GPRS data traffic

Average usage level

Time of day


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and ciphering. SGSN has also interaction with MSC and HLR. Interaction with MSC is

possible only if optional Gs-interface is in use.

The task of GGSN is to route packets to other packet networks (as internet) and packets

to individual mobile stations. GGSN also allocates IP addresses to mobile stations. From

the external networks’ point of view GGSN is just a router to a sub network because it

hides the GPRS infrastructure from the external networks. The Architecture of GPRS

capable GSM network is presented in Figure 3.

Figure 3: Architecture of GPRS capable GSM network

3.2. Protocol Architecture

As GPRS support is added to the network, a new set of protocols is needed [2].

Interworking between the new network elements is done with these new protocols. The

protocols used between MS and BSS (where link adaptation is working) are the physical

and RLC/MAC layer. GPRS protocol architecture is presented in Figure 4.

Figure 4: GPRS Protocol architecture

BTS MS BSC+PCU HLR

AuC

EIR

PSTN

Base Station Subsystem Network Switching

Subsystem

Air A-bis A-ter

BTS

MSC/VLR TC

A

SGSN

Gb

GGSN

Internet

Gr

Gn

Gs

IP IP

LLC

SNDCP

LLC

SNDCP

Physical

layer

Physical

layer

Air

MS BTS

L1bis

Network

service

BSSGP

L1bis

Network

service

BSSGP

Gb

SGSN

GTP

TCP or

UDP

IP

L1

L2

GTP

TCP or

UDP

IP

L1

L2

Gn

GGSN

RLC/ MAC

Abis L1 Abis L1

Abis

BSC + PCU

RLC/ MAC


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Physical layer is divided in two parts: physical RF-layer and physical link layer. 3GPP

reference configuration of the transmission chain of the physical layer is presented in

Figure 5 [3]. Physical RF-layer performs the modulation of the signal based on the bits

received from physical link layer. The same GMSK-modulation which is used in circuit

switched GSM is used also in GPRS. As a physical resource the system uses a part of the

radio spectrum dedicated for GSM. The most used GSM frequency bands are 850 MHz-,

900 MHz-, 1800 MHz- and 1900 MHz-band (there are also other bands specified for

GSM in [3]). For example GSM-900 frequency band means in practice 890 – 960 MHz

frequency range, where 890 – 915 MHz range is reserved for uplink and 935 – 960 MHz

range for downlink (FDD). The frequency band is divided into 124 channels that are 200

kHz apart from each other (FDMA). On every channel there are eight TDMA timeslots.

The physical link layer provides service for information transfer over a physical channel

between MS and the network. Most important services of physical layer are: Forward

Error Correction (FEC), synchronization, monitoring radio link quality, power control

and battery saving procedures (e.g. discontinuous reception). Four coding schemes are

defined for the packet data traffic channel: CS-1 – CS-4. They all have different code

rates resulting different error correction and throughput capabilities.

Figure 5: 3GPP reference configuration of the transmission chain of the physical layer [3]

RLC/MAC-layer offers reliable radio link to the upper layers. MAC (Medium Access

Control) layer takes care of radio connection management by defining the procedures that

enable multiple MSs to share a common transmission medium. On top of RLC/MAC

there is Logical Link Control Layer (LLC). It offers secure and logical link between MS

and SGSN. RLC (Radio Link Control) layer takes care of segmentation and reassembly

of LLC Packet Data Units (PDU). RLC layer has two transfer modes: acknowledged

mode and unacknowledged mode. In acknowledged mode RLC provides reliable service

Convolutional

coding

Block

coding

Reordering

and

partitioning

Inter-

leaving

Burst

multiplexing

Burst

building

Differential

encoding Modulation Transmitter

Receiver

Antenna

Information bits

(receive)

Air

interface

Information bits

(transmit)

Cryptological

unit (not used in GPRS)


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by using selective retransmissions for erroneous blocks. In unacknowledged mode

erroneously received RLC blocks are not retransmitted.

RLC throughput performance with different coding schemes is presented in Table 1.

Maximum transfer bit rate per one timeslot (TSL) for GPRS data is 8,0 kbit/s for CS-1,

12,0 kbit/s for CS-2, 14,4 kbit/s for CS-3 and 20,0 kbit/s for CS-4. As the bit rate

increases, the robustness gets worse. Link adaptation algorithm decides which of the

codecs is the most suitable in the current situation i.e. which coding scheme offers the

highest throughput in the current radio conditions.

Table 1: GPRS Coding Schemes

Coding Data rate

Data rate per TSL

excl. RLC/MAC Data rate

Data rate / 4 TSLs

excl. RLC/MAC

scheme per TSL headers per 4 TSLs headers

CS-1 9.05 kbit/s 8 kbit/s 36.2 kbit/s 32.0 kbit/s


CS-3 15.6 kbit/s 14.4 kbit/s 62.5 kbit/s 57.6 kbit/s


3.3. Mobile Stations

GPRS requires support from both the network and mobile stations. On MS side there are

three classes for GPRS mobile stations: Class A, B and C. Class A mobiles can use

simultaneously both packet and circuit mode connections. Class B mobiles don’t support

simultaneous traffic but are able to automatically switch the operation mode between

packet and circuit mode. These mobiles can be at the same time attached to GPRS and

GSM services. Class C devices can be attached to either GPRS or GSM network. The

devices may only be capable of using just one of the services but if they can use both

GSM and GPRS service, the selection between the services is done manually. The most

mobile stations on the market today are Class B equipment.

Mobile stations can usually use several timeslots for downlink and uplink data transfer.

This was possible already in the circuit switched GSM with HSCSD (High Speed Circuit

Switched Data). In GPRS the multislot class of the MS determines the maximum number

of timeslots the MS is capable to use simultaneously [Appendix B]. This multislot

capability is defined separately for DL and UL but also a maximum number of all used

timeslots (UL+DL) is defined. Nowadays Multislot Class 10 mobiles are very common.

They can use at maximum 4 timeslots for downlink and 2 for uplink but only 5 timeslots


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in all. That gives 80 kbit/s maximum bit rate for downlink and 40 kbit/s for uplink. The

bit rates presented here are RLC-layer bit rates, the application bit rate is lower due to

protocol overhead. Theoretical maximum bit rate for GPRS is 160 kbit/s with eight

timeslots.

3.4. Mobility Management

Mobility management in cellular networks is an essential feature. It makes it possible to

use the network services in the whole network not just in the cell where MS attached to

the GPRS service. The mobility management of GPRS is very similar to the one of GSM.

One or more cells form a routing area (RA) which is served by one SGSN. One routing

area is a subset of one location area.

Tracking of the mobile in the network depends on the mobile’s mobility management

state. There are three different states in mobility management [2]: idle, standby and ready.

The idle state is used when the user is passive and not attached to the GPRS network. In

this state the MS is not reachable by the GPRS network. In order to change the state and

be able to use GPRS the MS has to perform a GPRS attach procedure. The standby state

is used when the user has ended an active phase. The subscriber is still attached to the

mobility management and the location of the MS is known by the network within the

accuracy of a routing area. If MS sends data, it moves to ready state. The ready state is

used when MS is transmitting or it has just been transmitting data to the network. In ready

state SGSN is able to send data to MS without paging because the location of the MS is

known within the accuracy of a cell. In a GPRS detach procedure the MS moves back to

idle state. The GPRS detach procedure can be initiated by the MS or by the network. The

state transitions are presented in Figure 6.

Figure 6: MS GPRS Mobility Management States

IDLE READY STANDBY

GPRS attach

GPRS detach PDU transmission

Ready timer expiry or

Force to STANDBY


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When the MS moves in the network, its location information has to be updated. MS

performs a cell update when it changes cell within a routing area in ready-state. When

changing the cell to a new routing area in ready- or in standby-state, MS performs a

routing area update. There are two types of RA updates: intra-SGSN and inter-SGSN RA

update. If the new routing area is managed by the same SGSN as the old one, an intra-

SGSN RA update is used. If the new RA is managed by different SGSN, an inter-SGSN

RA update is used. When MS stays a long time in the same cell, the network has to know

that the MS is still reachable. In this situation periodic routing area update is made.

The mobility management state of the mobile has an effect also on the performance and

latency of the service because the procedures needed for sending and receiving data are

different in different states.


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4. Enhanced Data Rates for GSM Evolution (EDGE)

Wireless data has become an important service of mobile networks and demand for more

bandwidth has been growing all the time. ETSI started standardization of a new data

service that would offer higher bitrates than GPRS and finalized it in 1999. The new

service was called Enhanced Data Rates for GSM Evolution (EDGE).

EDGE offers great improvement to GSM data services by enhancing the data rates per

timeslot for multislot High Speed Circuit Switched Data (HSCSD) and GPRS. These

enhancements are called ECSD (Enhanced Circuit Switched Data) and EGPRS

(Enhanced General Packet Radio Service). In ECSD the maximum data rate is 64 kbit/s

due to limitations on the A-interface [2]. The throughput per timeslot is tripled when

compared with normal CS data, though. The ECSD throughput is quite low when

comparing it with EGPRS. The theoretical maximum throughput with EGPRS and eight

timeslots is 473 kbit/s (59 kbit/s per timeslot). This thesis will only concentrate here on

EGPRS because it has been more popular technology among the manufacturers than

ECSD.

4.1. Enhancements to GPRS

The design principle of EGPRS was to minimize the changes on GPRS specifications [4].

That minimizes the required chances to the network and makes sure that EDGE operates

easily with basic circuit switched GSM and GPRS. The carrier symbol rate (270,833

ksymbols/s), carrier pulse shape, burst duration and spectrum mask are the same for GSM

and EDGE [2] [5]. This ensures that EDGE and GSM can be used simultaneously in the

same cell and frequency (channel) but in different timeslots. EGPRS is built on top of

GPRS and therefore it’s quite easy to implement it to GPRS networks. EGPRS has major

impact on RF and physical layer, Abis-interface and some impact on RLC/MAC

protocols but the changes to other layers and protocols are minor [2].

The physical- and RLC/MAC-layer modifications were made to be able to offer higher

throughput. There are several enhancements in EGPRS in comparison to GPRS [6]: 8-

phase shift keying (8-PSK) modulation, 9 modulation and coding schemes, EGPRS link

adaptation, incremental redundancy (IR) hybrid automatic repeat request (HARQ) and

improved RLC/MAC retransmissions.


19

The main reason why EDGE is able to triple the throughput per timeslot (with good link

quality) is the change of modulation from Gaussian Minimum Shift Keying (GMSK) to

8-PSK. In GMSK modulation the symbols are represented by changing the phase by - π/2

or + π/2. Each symbol carries thus one bit. The direction of the phase change determines

if the bit is 0 or 1. In 8-PSK modulation the phase is shifted by -13/8 π, -9/8 π, -5/8 π, -1/8

π, +1/8 π, +5/8 π, +9/8 π or +13/8 π. This means that three bits are mapped onto one

symbol. That makes it possible to transmit three times as many bits as with GMSK (see

Figure 7).

Figure 7: 8-PSK constellation vs. GMSK constellation

As 8-PSK signal is able to transfer more data than GMSK signal, it also needs stronger

signal because of more challenging reception. In other words, if signal strength is low or

there’s much interference, GMSK codecs provide better throughput. Therefore, EDGE 8-

PSK modulation’s highest data rates can be achieved only with limited coverage when

compared to GMSK modulation.

There’s difference in maximum transmit power between modulations: GMSK-modulation

has 2-3 dB and 3-6 dB higher average power than 8-PSK modulation on downlink and

uplink direction, respectively. This is due to the fact that the EDGE transceiver has to

fulfill the same norms as normal GMSK-transceiver: the heat dissipation and transmit

spectrum have to be acceptable [5]. 8-PSK is also more challenging modulation than

GMSK from transceiver point of view: in contrast to GMSK, 8-PSK has varying

envelope and therefore the mean output power has to be lower than with GMSK to

achieve amplifier linearity.

EGPRS has nine different Modulation and Coding Schemes: MCS-1 – MCS-9. MCS-1 –

MCS-4 use GMSK as modulation and MCS-5 – MCS-9 use 8-PSK as modulation. The

different modulation and coding schemes are presented in Table 2 [7]. Link adaptation

Q

I

(1,1,0)

(1,0,0)

(1,0,1)

(0,0,1)

(0,0,0)

(0,1,0)

(1,1,1)

(0,1,1)

Q

I (1)

(0)

GMSK 8-PSK

1 bit/symbol 3 bits/symbol


20

selects the best MCS for the current radio conditions. With good link quality MCS-9 is

used and with poor quality MCS-1 is used. The lower the modulation and coding scheme

is, the more robust it is. EDGE has also Incremental Redundancy (IR) to improve the

performance of link adaptation. IR is explained in Chapter 6.2. This thesis concentrates

on EGPRS link adaptation and it is discussed more thoroughly in Chapter 6.

Table 2: EGPRS modulation and coding schemes

Scheme Modulation Data rate Data rate Code Header Blocks per Family

per TSL per 4 TSLs rate code rate 20 ms

MCS-9 59.2 kbit/s 236.8 kbit/s 1.0 0.35 2 A

MCS-8 54.5 kbit/s 218 kbit/s 0.92 0.35 2 A

MCS-7 44.8 kbit/s 179.2 kbit/s 0.76 0.35 2 B

MCS-6 29.6 kbit/s 118.4 kbit/s 0.49 0.33 1 A

MCS-5

8-PSK

22.4 kbit/s 89.6 kbit/s 0.37 0.33 1 B

MCS-4 17.6 kbit/s 70.4 kbit/s 1.00 0.5 1 C

MCS-3 14.8 kbit/s 59.2 kbit/s 0.80 0.5 1 A

MCS-2 11.2 kbit/s 44.8 kbit/s 0.66 0.5 1 B

MCS-1

GMSK

8.8 kbit/s 35.2 kbit/s 0.53 0.5 1 C


21

5. Performance of EGPRS

It’s an essential matter concerning this thesis to understand how the maximal

performance in packet based wireless networks (like EGPRS) can be reached. The overall

performance of wireless networks is highly affected by the performance of the Air-

interference: more than 60% of the latency is created there [8]. That is the reason why it’s

important that link adaptation works optimally.

The data rates presented in Table 2 are the maximum throughput values that can be

achieved on the RLC layer with continuous data transfer. These maximum throughput

values differ from the end-user throughput [9]. Figure 8 illustrates a case with TCP data

transfer. End-user throughput is only a part of the maximum throughput. Data link effects

and upper layer effects will reduce throughput available for the user. Data link effects are

the set of factors that depend on the network conditions such as interference, timeslot

multiplexing and RLC signaling. Upper layer effects are dependent on the transportation

and application protocols (e.g. TCP, HTTP and FTP) used by each service.

Figure 8: End-user performance with TCP data transfer

Continuous data transfer can be achieved only after certain initiation and transfer

procedures [10]. A sample of mobile originated data transfer procedures is presented in

Figure 9. When MS wants to send data, it first has to perform GPRS attach and activate

PDP context. Then packet channel request is needed to be able to start sending and

receiving data. Only during continuous data transfer the maximum throughput can be

achieved.

End-user throughput

TSL capacity

Data link throughput

Interference

Multiplexing

RLC signaling

Upper layer overheads

TCP establishment

TCP slow start

Cellular events & TCP

Application layer

Data link

effects

Upper-layer

effects

Maximum throughput


22

Figure 9: Mobile-originated data transfer in GPRS/EGPRS [18]

During data transfer TCP with its congestion control has great effect on the end-to-end

performance. TCP was originally designed for wireline networks [11]. In mobile

environment this can cause some problems because of the different characteristics of

wireline and wireless networks. The biggest difference between wireline network and

wireless EGPRS network is the larger round trip time (RTT) in EGPRS networks. This

has effect on the behavior of the TCP congestion control.

The operation of TCP congestion control is illustrated in Figure 10. First the slow start

algorithm of the TCP slows down the data transfer at the beginning of the transmission

because the congestion status of the network is not yet known. If no packet losses occur,

the TCP congestion window size will be increased step by step towards the maximum

(defined at the beginning of TCP transfer). In wireless networks the slow start phase takes

much longer time than in wired networks because it takes more time for the TCP

transmitter to receive acknowledgement messages for the sent packets (because of big

RTT). In slow start phase the TCP window size can be increased only after previously

sent packets are acknowledged. If one of the packets is lost during data transfer, TCP

interprets it as network congestion and reduces sending rate drastically.

In wired networks it is mostly network congestion that causes packet losses. In wireless

networks also the packet losses caused by poor link quality are interpreted by TCP as

network congestion which causes unnecessary reduction of throughput. This problem

doesn’t exist in EGPRS as RLC (in ACK-mode) takes care of the retransmissions [12] but

the problem of data losses is translated into variable RTT (caused by varying number of

RLC retransmissions).

Packet channel request

Packet immediate assignment

Packet resource request (optional)

Packet resource assignment (optional)

Data transmission

ARQ, feedback, channel coding change command

Data transmission

MS Network

Arrival of

Layer 3

data

Attach procedure

Context activation, link

establishment


23

TCP maintains a timeout timer for the sent packets. The length of this timer depends on

the RTT measured by the TCP transmitter. In cell changes or when the link quality

decreases dramatically, RTT is increased suddenly. This sudden increase can cause TCP

timeout [13] and then the TCP congestion window size is set to 1 MSS (Maximum

segment size) and the slow start phase is started again.

Figure 10: TCP congestion window

On top of TCP, that is, on the application layer for example HTTP or FTP can be used.

They both create overhead and require their own initiation procedure before continuous

data transfer can be achieved.

All these different characteristics of signaling, TCP, FTP and HTTP affect the end-user

performance as illustrated in Figure 8 and need to be taken into account when optimizing

the performance of the system. By understanding the protocol behavior it’s also possible

to estimate the maximum theoretical end-user performance in different scenarios.

Slow-start

threshold

Threshold

Linear increase

Exponential

increase

t

Window

size

Packet loss

Linear increase


24

6. EGPRS Link Adaptation

The radio path in wireless communication systems is a challenging environment for

mobile equipment. It requires far more complex and sophisticated measures from

equipment than the wired networks. There are several phenomena that affect the quality

of radio path: attenuation, noise, interference and fading [14]. Attenuation and noise are

familiar phenomena also in wired networks but they are far more significant in wireless

networks than in wired ones. Interference and fading, on the other hand, are not very

common in wired networks. Interference to the radio signal is caused by other equipment

that are using the same frequency somewhere near enough. In GSM networks interference

is caused by base stations (BTS) and mobile stations (MS). Fading is a phenomenon that

is caused by the distortion that the signal experiences over certain propagation media. The

most common types for fading are fast fading and slow fading. Fast fading is known also

as multipath propagation fading. It results from the superposition of transmitted signals

that have traveled different paths to the receiver reflecting e.g. from buildings and

ground. Different paths cause different attenuation, delay and phase shift in every signal

component. Fast fading is caused by small movements of a mobile. Also scatterers around

a (stationary or moving) mobile cause fast fading. Slow fading, on the other hand, is large

scale fading that is caused by for example obstructions in propagation environment.

6.1. Operation of Link Adaptation

The task of link adaptation is to optimize the EGPRS performance with respect to the

quality of the radio path. Link adaptation works on the Air-interface, between MS and

BTS and is controlled by BSC. The link conditions on the Air-interface can change from

good receive quality with line of sight to the base station to very challenging conditions

far away from the base station with high interference. These changing conditions require

ability from the system to adapt to the current radio environment. In very good conditions

with high received power level (RX-level) and low interference there is not much need

for error correction and most of the available bits in the RLC block can be used for user

data. On the other hand, when the conditions are poor (low RX-level, high interference),

the system has to sacrifice many of the bits for error correction, and when the conditions

get poor enough, even the modulation has to be changed to be able to get the wanted data

through the network without errors. The task of the link adaptation is to maximize the

throughput in all different conditions.


25

The way how link adaptation adapts to the current radio conditions is that it changes the

coding and modulation based on the link quality information reported by MS and BTS.

More robust codecs are selected when the link quality gets worse and less robust codecs

are selected when the quality gets better. When bit rate is high, the robustness to time

dispersion and MS’s speed is decreased because of small amount of error correction [5].

When more robust coding is needed, the user bit rate is decreased because the only way to

be able to receive the transferred data correctly is to increase the amount of redundancy.

This variability in coding is made possible (as stated earlier) by using nine different

modulation and coding schemes, all with different amount of error correction and two

modulations. The nine different modulation and coding schemes are MCS-1 – MCS-9.

MCS-1 is the most robust scheme and MCS-9 the least robust scheme (offering the

highest bit rate in good conditions). Figure 11 shows the performance of different MCSs.

LA algorithm has to choose the right MCS for different situations. The ideal link

adaptation would follow the envelope of throughput of different MCSs [15] selecting the

MCS with the highest throughput. In practice, the link adaptation chooses the MCS that

meets best the predefined criteria.

Figure 11: Performance of different MCSs from [4]

The Automatic repeat request (ARQ) procedure in EGPRS is based on selective

retransmission of erroneous packets [16]. If data blocks are not received correctly, they


26

are retransmitted. In the retransmissions also the Incremental Redundancy (IR) is usually

used [2].

There are three families within MCSs: A, B and C. These determine the possible codecs

that can be used on retransmissions: the retransmission has to be performed with an MCS

that belongs to the same family with the MCS of the original transmission. MCS-9, MCS-

8, MCS-6 and MCS-3 belong to family A, MCS-7, MCS-5 and MCS-2 to family B and

MCS-4 and MCS-1 to family C. Within every family there is some similarity between the

payload sizes which makes it possible to resegment the block for retransmissions [17]. In

Nokia’s solution it is not possible to resegment the RLC blocks. This restricts the

retransmission to use the same modulation as in the original transmission. The MCS

choice in retransmission with and without re-segmentation is specified in [18]. The block

structure of different MCSs is presented in Figure 12.

Figure 12: Block structure of MCS-1 – 9

6.2. Incremental Redundancy

The Incremental Redundancy (IR) used in retransmissions improves EGPRS’s

performance compared to GPRS by introducing 0-3 dB gain to system performance [15].

IR improves the performance especially if LA is not working optimally or the link quality

measurements are not perfect [16].

MCS-7

MCS-1 22 MCS-2 28 MCS-3

37 MCS-4 44 MCS-5 56 MCS-6 74

56 56 MCS-8

68 68 MCS-9

74 74

redundancy from channel coding

RLC data block, number of bytes

RLC/MAC block (radio block)

11.2 kbps

14.8 kbps

17.6 kbps

8.8 kbps

22.4 kbps

29.6 kbps

44.8 kbps

54.4 kbps

59.6 kbps

GMSK

8-PSK


27

IR is working by adjusting the code rate to actual channel conditions by incrementally

sending redundant data until the decoding is successful. In addition the receiver has to

store all the failed transmissions to be able to combine the different versions of the

transmission [19]. Figure 13 shows how the IR is working when MCS-9 is used. First the

data is convolutionally encoded with coding rate 1/3. Before the first transmission 2/3 of

the bits are punctured. That leads to basic code rate 1. It means that the same number of

bits is transmitted as was in the original data. While the retransmissions are done, the

code rate drops to 1/2 after the first retransmission and 1/3 after the second

retransmission. After the second retransmission we have three times as much bits as the

original transmitted data contained, so we have increased the redundant information. That

increases the probability to receive the bits correctly. To be able to operate, IR needs

successful reception of header information [4]. That is the reason why headers are coded

more robustly than data parts (see Table 2). If the header is not received properly, the IR

is unable to operate because the receiver doesn’t know to which packet the transmission

belongs.

Figure 13: IR transmission and combining with MCS-9

6.3. Bit Error Probability as Channel Quality

Criterion

Link adaptation needs link quality reports from MS and BTS to be able to adapt to the

changing conditions. In EGPRS the link quality is measured in terms of Bit Error

Probability (BEP) [20]. BEP expresses the probability of having a bit error and it is

determined based on the soft values from the receiver reception (soft values are the raw

bit values interpreted from the received symbols). The receiver (in BTS and MS)

original data

1/3 coded data

1st xmission

2nd xmission

3rd xmission

1st decoding attempt

2nd decoding attempt

3rd decoding attempt

r = 1/3

r = 1/2

r = 1/1

r = 1/1

r = 1/1

r = 1/1


28

measures the BEP values on every TDMA burst and computes two measurement values,

namely mean BEP and CV_BEP (i.e. coefficient of variation of BEP), for each RLC

block (one block consists of four bursts) as follows:

∑=

=4

14

1_

i

iburstblockBEPBEPMEAN (1)

∑

∑ ∑

=

= =

−

=4

1

24

1

4

1

4

1

4

1

3

1

_

i

iburst

k i

iburstkburst

block

BEP

BEPBEP

BEPCV (2)

Where BEPburst i is the BEP of ith burst, MEAN_BEPblock is the mean BEP averaged over a

block, CV_BEPblock is the CV_BEP for a block, i is the number of burst in a block and k

is the number of burst in a block.

After this the mean BEP and CV_BEP values are averaged over a measurement period.

The duration of this period can vary from 1 block duration to 25 block durations. The

averaging is done to every timeslot and modulation type separately as shown below:

0R ,xeRe)(1R 1n1nn =⋅+⋅−= −− (3)

nblock,n

n1n

n

nn MEAN_BEP

R

xeNMEAN_BEP_T)

R

xe(1NMEAN_BEP_T ⋅⋅+⋅⋅−= − (4)

nblock,n

n1n

n

nn CV_BEP

R

xeCV_BEP_TN)

R

xe(1CV_BEP_TN ⋅⋅+⋅⋅−= − (5)

Where n is the iteration index, incremented per each radio block, MEAN_BEP_T Nn is

the average of mean BEP of one TSL during measurement period, CV_BEP_T Nn is the

average of CV_BEP of one TSL during measurement period, Rn denotes the reliability of

the filtered quality parameters, e is the forgetting factor (depending on measurement

period) and xn denotes the existence of quality parameters for the nth block (i.e. if the

radio block is intended for this MS; xn values 1 and 0 denote the existence and absence of

quality parameters, respectively).


29

Finally the BEP-values are averaged over used timeslots for each modulation separately

as shown below:

∑

∑ ⋅

=

j

(j)

n

j

(j)

n

(j)

n

nR

NMEAN_BEP_TR

MEAN_BEP (6)

∑

∑ ⋅

=

j

(j)

n

j

(j)

n

(j)

n

nR

CV_BEP_TNR

CV_BEP (7)

Where MEAN_BEPn is the average of mean BEP during measurement period, CV_BEPn

is the average of CV_BEP during measurement period, n is the iteration index at

reporting time and j is the channel number.

These BEP measurements, namely MEAN_BEPn and CV_BEPn for GMSK modulation

and MEAN_BEPn and CV_BEPn for 8-PSK modulation, are used as an input for link

adaptation. In uplink data transfer the link adaptation receives these BEP measurements

from the BTS and in downlink data transfer these values are received from the MS in DL

ACK/NACK message.

6.4. Link Adaptation Algorithm

The BSC uses look-up tables in selecting the MCS based on BEP reports. The input

information used in the look-up tables are the MEAN_BEP and CV_BEP measurements

received from the receiver (MS or BTS). There are three different look-up tables:

Modulation selection table, 8-PSK MCS selection table and GMSK MCS selection table.

The link adaptation algorithm is presented in Figure 14. First the modulation type

decision is made between GMSK and 8-PSK. If the received BEP values indicate poor

link quality, GMSK-modulation should be used and if the BEP values indicate good

quality, 8-PSK-modulation should be used. When GMSK is chosen as modulation, the

MCS is selected from the GMSK MCS selection look-up table. When 8-PSK is chosen as

modulation, the MCS is chosen from the 8-PSK MCS selection table. This chosen MCS

is then used for data transmission until new BEP reports are received and link adaptation

algorithm is used again in deciding the new MCS. In Table 3 there’s an example of the

look-up table for 8-PSK MCS-selection from 3GPP specification [20].


30

Figure 14: Link adaptation algorithm

Note that BEP measurements are needed for both modulations but if only one modulation

is used during a measurement period, only BEP-values for the used modulation are

received. In that situation we need to convert these values to other modulation’s BEP

values in order to use the look-up tables as described. So also look-up tables for

conversions from 8-PSK BEP values to GMSK BEP values and from GMSK BEP values

to 8-PSK BEP values are needed. During 8-PSK data transfer GMSK BEP-values are

usually received because RLC control blocks use always GMSK. The above-mentioned

conversion tables are needed especially when using GMSK modulation as no 8-PSK BEP

values are received during GMSK data transfer.

In the beginning of transmission the link quality and BEP-values are not known by the

BSC until the first measurement reports are received. Until then BSC is using predefined

MCS. This predefined MCS can be adjustable or fixed. The initial MCS affects quite

much to the performance of the network because the link adaptation is not working until

the first reports are received. If this MCS is too high, there are problems when the link

quality is poor. On the other hand if the initial MCS is too low, it reduces the performance

when the link quality is good.

Table 3: MCS selection table for 8-PSK from 3GPP specification [20]

8-PSK MEAN BEP

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

1 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 7 7 7 8 8 8 8 8 8 9 9 9 9

2 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 7 7 7 8 8 8 8 8 8 9 9 9 9

3 5 5 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9

4 5 5 5 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9

5 5 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9

6 5 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9

7 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9

8-PSK CV BEP

8 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 9 9 9 9

Selection of

modulation

Selection of

GMSK MCS

Selection of

8-PSK MCS

GMSK chosen as modulation

8-PSK chosen

as modulation

Chosen MCS

(MCS-1 – 4)

Chosen MCS

(MCS-5 – 9) GMSK Mean BEP

8-PSK Mean BEP

GMSK CV BEP

8-PSK CV BEP


31

7. Test Scenarios for EGPRS Link Adaptation

Measurements

To be able to optimize the performance of the current link adaptation some test

measurements have to be done to see what the current system’s potential for improvement

is. First the test scenarios and cases for verifying the performance of the current LA need

to be defined. The same tests will later be made with optimized solutions to verify the

possible improvement in performance.

When designing the test cases, the emphasis has been on the end-user perspective. In the

tests the performance experienced by the user is to be verified. If any problems are found,

some other more detailed measurements are needed to get deeper understanding of the

way the system works and to identify the root cause for the non-optimal behavior.

A laboratory network and a live GSM test network are in use for these EGPRS LA tests.

The radio conditions in the live network are of course more realistic than the radio

conditions in the laboratory network but in the laboratory it’s possible to make more

accurate and repeatable measurements. The laboratory conditions are more stable and that

makes it possible to see the effect of changes made to the system more reliably. The live

network can be used to test and verify the final changes made for LA. There it can be

seen if the real impact of the changes was the same as intended and the same as in the

laboratory. That is important because the changes to the system, if they are successful, are

aimed to be used in real operators’ live networks.

In all laboratory measurements Nokia MetroSite base station (BTS) and Nokia BSC2i

(BSC) were used. The measurements were done in 1800/1900 MHz band. Signal

generator, spectrum analyzer and Propsim fading simulator [21] were used to support the

laboratory measurements. Signal generator was used in the measurements as a source of

interfering signal. Spectrum analyzer was used to analyze the signal level and signal’s

spectrum. Fading simulator was used for simulating multipath propagation of the signal

on the Air-interface. The MSs used in the tests were mostly Multislot class 10 devices

(max. 4 downlink and max. 2 uplink timeslots used for EGPRS) [Appendix B]. Some

other class MSs were used in the final verification of new EGPRS LA. The MSs used in

the tests were Rel4 and Rel99 phones (Rel4 MS meeting the requirements of GSM

Standard version Release 4 and Rel99 MS meeting the requirements of GSM Standard

version Release 99). Frequency hopping was not used in the tests. The configuration of

the laboratory network is presented in Figure 16.


32

Figure 16: Laboratory access network

7.1. Laboratory Test Scenarios

In the laboratory there are three different types of scenarios: variable RX-level, variable

Carrier-to-interference (C/I) and fading with variable RX-level. The variable RX-level

scenario represents coverage limited scenario as all interference is noise [15]. In that

scenario only the RX-level from the BTS and MS is attenuated. The RX-level range is -

50 dBm – -108 dBm. No additional interference is added to the signal.

The variable C/I scenario represents capacity limited scenario as interference is added to

the signal and noise is not the dominant component. In that scenario RX-level is set to

stable -70 dBm and interference is generated by GMSK modulated signal. The

interference is attenuated so that the C/I-ratio is between 0 dB and 35 dB.

In the fading scenario (with variable RX-level) 3GPP specified 6-tap propagation models

[22] TU3 (Typical urban 3 km/h) and TU50 (Typical urban 50 km/h) are created with

Propsim radio channel simulator. These models simulate the multipath propagation of the

signal (in other words fast fading) in the air interface. The models can be found in

[Appendix A]. These models are used to simulate the real network in the laboratory to see

if the behavior of the system with fading is the same as in variable RX-level and variable

C/I scenarios. If the behavior in the laboratory fading scenario was similar, it would

suggest that the changes made to LA should work also in real environment where

multipath propagation is common. Link adaptation itself is unable to react fast enough to

fast fading but Incremental Redundancy helps in these situations [23].

7.2. Laboratory Measurement Configurations

Variable RX-level scenario is a basic measurement scenario in mobile phone network

testing. It’s easy to implement as just the transmitting power of the BTS or the attenuation

on the Air-interface can be adjusted. In the laboratory, an attenuator on the Air-interface

MS BTS BSC SGSN GGSN Server


33

was used. The MS was placed into a shielded enclosure to avoid uncontrolled interference

from other laboratory or public networks. Rel4 MS was connected to the BTS with a

cable whereas Rel99 MS was connected to the BTS via normal Air-interface (in the

shielded enclosure) with its own antenna. The different kinds of Air-interfaces were used

to get more information about the behavior of LA in the measurements: cable-Air-

interface was more stable than the normal Air-interface whereas the normal Air–interface

represented better the “real” situation than the cable-Air-interface. The shielded enclosure

was connected with a cable to BTS’s transceiver. In that cable there were two attenuators:

one with constant 30 dB attenuation and one with variable 0 – 110 dB attenuation. The

measured RX-level range was from -50 dBm to -108 dBm. In both uplink and downlink

measurements the RX-level is the MS received power level (not BTS RX-level for

uplink). The MS RX-level is different from the BTS RX-level but to be able to compare

the uplink and downlink results the MS received power is used also in the uplink. The

reason for difference between MS and BTS received power-levels is the higher transmit

power of the BTS [24]. When MS RX-level is used in both UL and DL measurements,

the radio conditions (i.e. the location of the MS in a cell) remains the same regardless of

the data transfer direction. Configurations for variable RX-level scenarios are presented

in Figures 17 and 18.

Figure 17: Configuration for variable RX-level scenario with Rel4 MS

Figure 18: Configuration for variable RX-level scenario with Rel99 MS

0…110 dB Shielded test enclosure

BTS

Attenuator

Adjust MS RX-level

30 dB


BTS Adjust MS RX-level

30 dB

Attenuator

Attenuator

Attenuator


34

Measurements in variable C/I scenario are bit more complex to carry out than in variable

RX-level scenario but that scenario is a bit closer to the real situation in live networks

than variable RX-level scenario. In C/I scenario the carrier signal is interfered with

another signal. In the measurements for this thesis the interference signal was GMSK

modulated signal. The interference was added simultaneously only to either uplink or

downlink direction to be able to analyze UL and DL operation more precisely. The

interference was added to the direction where the most of the data was transferred. This

means that for uplink data transfer the interference was on the uplink frequency and for

the downlink data transfer the interference was on the downlink frequency. There was an

attenuator for the interferer so that it was possible to adjust the C/I (carrier power was

kept constant). The interference level was adjusted in the measurements according to the

GMSK-signal level although both 8-PSK and GMSK were used. This was done because

we wanted the absolute interference level to be the same for different modulations as in

the real network. Configurations for variable C/I scenarios are presented in Figures 19

and 20.

Figure 19: Configuration for variable C/I scenario, interference in downlink

Figure 20: Configuration for variable C/I scenario, interference in uplink


30 dB

BTS

Signal Generator

0…110 dB

I

C+I C

Adjust interference

Adjust MS RX-level

level Attenuator

Attenuator

Attenuator

C

I

C+I


30 dB

BTS

Signal Generator

Adjust MS RX-level

Adjust interference level

Attenuator

0…110 dB Attenuator

Attenuator


35

Measurements in fading scenario were done to simulate the live network with fading.

Propsim radio channel simulator was used to simulate fading. The fading was applied

only to one channel (UL or DL) to be able to adjust the signal levels easily. The fading

simulator is quite sensitive with the input signal levels so they needed to be adjusted

properly. The simulator takes the signal (to be altered) and RF local oscillator (RFLO) as

inputs. A signal generator was used as RF local oscillator and RFLO signal was adjusted

with -500 MHz offset to the real frequency (as defined in Propsim user manual): in these

tests that is 1,9894 GHz– 0,5 GHz = 1,4894 GHz for DL and 1,9094 GHz– 0,5 GHz =

1,4094 GHz for UL. The RFLO signal power was +10 dBm and the input signal was in

range -15 dBm - +10 dBm. As an output the simulator gave the altered faded signal. Also

circulators and isolators were used in this configuration to prevent the receiver (in MS or

BTS) from getting a stronger non-faded signal from other direction’s path. One circulator

or isolator causes 3dB attenuation in desired direction and 20 dB attenuation in other

direction. When downlink fading measurement was made, the downlink channel was

passed through the simulator and a variable attenuator whereas the uplink channel was

going directly to the BTS. During DL measurement the uplink channel was all the time in

good condition. Without the circulators the MS could have received a strong signal on the

uplink path and the DL path with fading would have been meaningless. In the uplink

measurements the downlink channel was in good condition and fading was done to the

uplink channel. In Figures 21 and 22 setup configurations for downlink and uplink

measurements are shown with used signal levels and attenuations.

Figure 21: Configuration for DL fading scenario with variable RX-level

0…110 dB

40 dB

BTS

Signal Generator

DL DL

UL

Radio Channel

RFLO

RF IN RF OUT

1

3

2 1 2 1 2 3

1

2

10 dB 30 dB Shielded test enclosure

Adjust MS RX-level

Simulator

Attenuator

Attenuator Attenuator Attenuator


36

Figure 22: Configuration for UL fading scenario with variable RX-level

7.3. Live Test Scenarios

The live tests were executed in Ruoholahti, Helsinki. There were two different scenarios

for live network tests: drive test scenario and stationary test scenario. In drive test

scenario the measurements were done while driving a route. The route on the drive test

was driven at normal traffic speed (under 40 km/h). Although the speeds in the tests were

not exactly the same as in the laboratory (3GPP-models TU3 and TU50), the drive tests

gave a good reference for the fading measurements that were done in laboratory network.

Figure 15 shows the route on a map.

The stationary tests were executed at three different locations: at RX-levels -80 dBm, -90

dBm and -100 dBm. Locations for the stationary tests and the used BTS are marked on

the map (in Figure 15) as well. The measurements were executed on the back lobe of the

BTS as it offered more variation in link quality in a smaller area than the main lobe of the

BTS.

The live measurements were done with Nemo Outdoor software and hardware [25]. This

application records all the events on the Air-interface. This makes it possible to analyze

different figures such as RX-level, C/I, used MCS and RLC throughput after the test

drive.

0…110 dB

40 dB

BTS

Signal Generator

UL

UL

DL

Radio Channel

RFLO

RF OUT RF IN

1

2

3 2 1 2 1 2

1

3

20 dB 30 dB

10 dB

Shielded test enclosure

Adjust BTS RX-level Simulator

Attenuator Attenuator

Attenuator Attenuator Attenuator


37

Figure 15: Live test driving route

7.4. Test Cases for Laboratory and Live Network

The measurements were made with three different applications: FTP-data transfer, HTTP-

data transfer and Ping. All these test measurements were executed with all different

scenarios and for Rel99 MS and Rel4 MS separately. These tests were mainly done to see

the behavior of the current system and to have some baseline measurements to which the

performance of the optimized LA could be compared.

As we are interested in end-user performance, the quality of service from the end-user

perspective was measured at the application level. FTP is a key application to measure

end-to-end throughput performance [15] and HTTP is widely used in web surfing. This is

why FTP and HTTP transfer measurements were chosen for throughput measurements.

These both protocols are using TCP which is the dominant protocol used in wired

networks and is becoming common also in packet based wireless networks.

In laboratory FTP throughput measurement tests were done with three different file sizes:

5 kB, 100 kB and 2 MB (DL) / 1 MB (UL). The files were non-compressible (e.g. zip-

files) so that the network elements handling the file were not able to improve the

performance by compressing the file. The measurement results were averaged over 3 – 5


38

measurements. FTP data transfer cases were measured with a laptop. HTTP download

tests were done with 100 kB-html-page with 16 objects. The HTTP download for the

whole 100 kB-html page was measured with Microsoft Internet Explorer 6 [26].

4s HTTP download test was executed by downloading a html-page over HTTP and

measuring the amount of data that is received during the first four seconds of the data

transfer. The results were averaged over ten measurements.

Round trip time (RTT) is a key element when evaluating end-user performance. The

latency in the network affects directly to the quality of service: setup delay, TCP and

other upper layer protocols’ performance and service interactivity [9]. The RTT

measurements were done as active and idle. In both measurements the MS had performed

GPRS attach and PDP context activation before the RTT measurements. Active RTT

measurements mean that the MS sends ping-packets so often that new TBF (Temporary

Block Flow) doesn’t have to be created during different ping-packets. In idle RTT

measurements the time between the ping-packets is so long that TBF has to be created for

every packet separately.

RTT was measured with Ping application as an average over 100 samples with three

different packet sizes: 32 bytes, 256 bytes and 1460 bytes. The smallest packet gives a

good estimate for the minimum respond time whereas the biggest packet shows the

latency of a big packet. The RTT was measured between MS and gateway of the local

area network using Microsoft Windows XP’s built-in version of ping.

The summary of all test cases measured in the laboratory is presented in Table 4. All

these tests were done before and after the optimization.

Table 4: Laboratory test case summary

Laboratory Measurements

FTP-throughput measurements

HTTP-transfer measurements RTT measurements

5 kB 4 sec 32 Bytes

100 kB DL

100 kB 256 Bytes

DL

2 MB

Ping size:

1460 Bytes

5 kB

100 kB

UL

1 MB


39

In the live test network we concentrated as well on throughput and RTT tests. These both

tests were done as stationary tests and driving tests. In the stationary locations the

measurements were made with 3 different RX-levels: -80 dBm, -90 dBm and -100 dBm.

The driving tests were executed by driving a route which has variable RX- and

interference levels. The summary of all test cases measured in live network is presented

in Table 5.

Table 5: Live network test case summary

Live Network Measurements

FTP-throughput measurements

HTTP-transfer measurements RTT measurements

DL 2MB 4 sec 32 Bytes

UL 1 MB DL

100 kB 256 Bytes

Ping size:

1460 Bytes

Also other tests were needed to find out in what conditions the system is not working

optimally and what could cause this non-optimal behavior. To see how the ideal LA

should work the measurements with fixed MCSs were executed with variable RX-level

and variable C/I scenarios. The BEP values were also measured as a function of C/I

because LA algorithm uses BEP measurements when deciding the MCS. By measuring

the BEP values with different C/I values it is possible to find relation between BEP and

the best suitable MCS. That should be a way to optimize the look-up tables.

7.5. Earlier Measurements on Link Adaptation

There are already quite many measurements made at Nokia about the performance of

EGPRS link adaptation. These earlier measurements offer quite a good benchmark

database to our tests and results. The potential for EGPRS LA performance improvement

was actually seen in these earlier made tests.

The reason why the current EGPRS LA is not working optimally (i.e. it’s not choosing

most suitable MCSs) in all situations seems to be, according to these earlier tests, that LA

uses too high MCSs. This doesn’t cause problems when the link quality is good but when

it gets worse, the throughput starts to deteriorate more than it should. If lower codecs

were used, the performance would be better in poor radio conditions. It is believed that

there’s possibility and potential to improve the current system performance. As said


40

already in the introduction, the main goal for this thesis is to develop the EGPRS link

adaptation so that its performance would be closer to the optimal performance. The

performance of the LA should be improved with all applications (e.g. FTP-throughput,

Ping-RTT) especially when the link conditions are poor (low RX-level, low C/I). The

measurements with fixed MCSs, i.e. when EGPRS LA is disabled, offer a good reference

performance level. The performance of the system when link adaptation is used should be

as good as the best MCS’s performance at certain link quality level. It means that if at a

certain level MCS-3 offers the best throughput, also the link adaptation should use that

MCS.


41

8. Measurement Results and Optimization of Link

Adaptation

The measurements for optimizing the EGPRS link adaptation were executed in the

laboratory and in the live network. First the baseline measurements were done in the

laboratory and with the help of these measurements some changes to the system were

made and various different test software builds were created. After these changes, the

performance with the new software versions was measured and the best one was chosen

for further tests. The chosen version was then compared to the original EGPRS link

adaptation algorithm. Although the number of measured samples in the measurements

was quite low, the results should present quite well the real performance of the system.

Reliability of the measurement results is analyzed in [Appendix C].

The performance with most suitable MCSs (i.e. MCSs that offer highest throughput in

current situation) represents the performance level of optimal or ideal link adaptation.

This performance level is later in this thesis referred as optimal performance level. The

link adaptation that offers this optimal performance level is referred as optimal LA.

8.1. Baseline Measurement Results

The baseline measurements were executed according to the test plan in three different

laboratory scenarios: in variable RX-level scenario, in variable C/I scenario and in fading

scenario (with variable RX-level).

In this chapter we will go through the measurements results for the variable RX-level

scenario and variable C/I scenario concerning the data throughput and round trip time

(RTT). In these measurements the performance of the link adaptation algorithm is

compared with the performance of all MCS-codecs. The tests were done by first

measuring the performance with link adaptation enabled and then the performance of

every MCS was measured separately. This way we are able to see what is the optimal

performance level and whether the current link adaptation algorithm is able to reach it. In

the end of this chapter a summary of improvement potential of the current system is

presented. The measurement values for throughput and RTT measurements in this thesis

are presented relative to reference values for confidentiality reasons. In throughput


42

measurements the highest throughput value measured in the given scenario is used as a

reference level . Respectively, in RTT measurements the smallest RTT value measured in

the given scenario is used as reference level.

8.1.1. Measurements in Variable RX-level Scenario

In the variable RX-level scenario the RX-level was varied from -108 dBm to -50 dBm

and the end-user throughput was measured for each RX-level with FTP application. The

measurements were made separately for downlink and uplink direction (measurement

configuration is described in Chapter 7.2). The throughput was first measured with the

current LA algorithm and then without it using fixed MCSs. When link adaptation was

enabled, MCS-3 was used as an initial MCS in all tests.

The downlink throughput results obtained with the link adaptation algorithm and the

respective results with fixed MCSs in variable RX-level scenario have been plotted in

Figure 23. First we should analyze the difference in performance of the different MCSs.

In general it can be seen that throughput increases when the RX-level (i.e. the link

quality) increases. MCSs with high number (as e.g. MCS-9) offer better end-to-end

throughput than the MCSs with small number (as e.g. MCS-1) when the link quality is

good. When the link quality is poor, the situation is the opposite. The throughput of all

MCSs saturates when the RX-level increases high enough. The smaller the MCS number

is the smaller is the RX-level where the throughput saturates.

In downlink in the variable RX-level scenario the biggest performance difference

between the best fixed MCS and link adaptation is when the RX-level is below -100

dBm. The LA-algorithm seems to be unable to change to GMSK codecs (MCS-1 – MCS-

4) on these RX-level values. When the radio conditions get worse, FTP downlink

throughput deteriorates already when the RX-level is -102 dBm with LA. With fixed

GMSK codecs the FTP data transfer is possible down to -106 dBm. There is also some

room for improvement when the RX-level is reasonably high at -88 dBm – -90 dBm.

With these RX-level values the LA algorithm used MCS-9 even if the performance of the

MCS-8 was better than the performance with MCS-9.

The uplink throughput results obtained with the link adaptation algorithm and the

respective results with fixed MCSs in variable RX-level scenario have been plotted in

Figure 24. In the uplink the same kind of behavior can be seen as in the downlink

measurements. The LA is not using GMSK codecs even when the RX-level is below -95

dBm. With GMSK codecs the FTP data transfer was possible down to -106 dBm whereas


43

with 8-PSK it was possible only down to -100 dBm. The throughput difference between

the best fixed MCS and link adaptation is bigger than the respective difference observed

in the downlink measurements and the reason for this is the power backoff of the 8-PSK

modulation (compared to GMSK modulation) [27]. When the link quality is good, the

link adaptation algorithm is working optimally and choosing most suitable MCSs.

Figure 23: Downlink FTP throughput in variable RX-level scenario

Figure 24: Uplink FTP throughput in variable RX-level scenario

UL FTP Throughput, variable RX-Level, 2 TSL

0.00

0.20

0.40

0.60

0.80

1.00

1.20

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)

FTP Throughput (relative)

MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on

LA is unable to change to

GMSK modulation

DL FTP Throughput, variable RX-Level, 4 TSLs

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)


MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on

LA uses MCS-9 although MCS-8

would offer higher throughput LA is unable to change to

GMSK modulation


44

RTT in variable RX-level scenario was measured for the same RX-levels for which the

throughput was measured in this scenario. The measurement was done as active RTT

measurement and the size of the ping packet was 32 bytes.

The RTT results with the link adaptation algorithm and the respective results with fixed

MCSs in variable RX-level scenario are presented in Figure 25. The behavior of link

adaptation in RTT measurements is similar to the one seen in the throughput

measurements: when the link quality is good, link adaptation works well but when the

quality gets worse, LA is unable to change to GMSK codecs. The performance of link

adaptation is worse than the performance of the best fixed MCS when the RX-level is

below -95 dBm. With GMSK codecs the RTT times are still reasonable when the RX-

level of the link is as low as -106 dBm.

Figure 25: RTT with 32-byte-sized ping packet in variable RX-level scenario

8.1.2. Measurements in Variable C/I Scenario

The same tests that were done in variable RX-level scenario were done also in variable

C/I scenario. In the variable C/I scenario the C/I was varied from 0 dB to 35 dB. The

measurements were made separately for downlink and uplink direction (measurement

configuration described is in Chapter 7.2).

32B RTT, variable RX-Level

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)

RTT (relative)

MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on


GMSK modulation


45

In downlink in variable C/I scenario the LA was in some circumstances able to change to

GMSK codecs unlike in variable RX-level scenario. That made it possible to reach the

optimum performance level also when the link quality was very poor (C/I under 5 dB).

However, at the point where the modulation should have been changed, the throughput

deteriorated completely (C/I was around 6 dB). Also the same behavior, link adaptation

using MCS-9 when MCS-8 would have offered better throughput, was seen here as in

variable RX-level scenario. This happened with good link quality (at C/I values 18 – 25

dB). The downlink throughput measurement results in variable C/I scenario are presented

in Figure 26.

Figure 26: Downlink FTP throughput in variable C/I scenario

The uplink performance of link adaptation in variable C/I scenario had exactly the same

problems as LA in the variable RX-level scenario: when the C/I is under 10 dB, the

performance of the link adaptation is below the optimum level. The uplink FTP data

transfer results in variable C/I scenario are presented in Figure 27.

DL FTP Throughput, C/I, 4 TSLs

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 5 10 15 20 25 30 35

C/I (dB)


MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on

LA is unable to change to GMSK

modulation early enough LA uses MCS-9 although MCS-8

would offer higher throughput


46

Figure 27: Uplink FTP throughput in variable C/I scenario

RTT in variable C/I scenario was measured with the same C/I-ratios with which the

throughput was measured in this scenario. The measurement was done as active RTT

measurement and the size of the ping packet was 32 bytes.

The RTT measurement results in variable C/I scenario in downlink are presented in

Figure 28 and RTT measurement results in variable C/I scenario in uplink are presented

in Figure 29. The RTT measurements provided similar results as the RTT measurements

in the variable RX-level scenario. When the C/I is under 10 dB, the link adaptation is not

working optimally: GMSK is hardly used.

UL FTP Throughput, C/I, 2 TSL

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 5 10 15 20 25 30 35

C/I (dB)


MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on


GMSK modulation


47

Figure 28: RTT with 32-byte-sized ping packet in variable C/I scenario, interference in downlink

Figure 29: RTT with 32-byte-sized ping packet in variable C/I scenario, interference in uplink

32B RTT, C/I in DL

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

0 5 10 15 20 25 30 35

C/I (dB)

RTT (relative)

MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on


modulation early enough

32B RTT, C/I in UL

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

0 5 10 15 20 25 30 35

C/I (dB)

RTT (relative)

MCS=1

MCS=2

MCS=3

MCS=4

MCS=5

MCS=6

MCS=7

MCS=8

MCS=9

LA on


GMSK modulation


48

8.1.3. Improvement Potential of the Current Link

Adaptation

The biggest opportunity to improve the current link adaptation algorithm is to optimize

the selection of MCS when the link quality is poor. The link adaptation algorithm is

unable to choose GMSK codecs even if the link quality is not good enough for 8-PSK

codecs. The situation when this behavior causes problems is when RX-level is below -

100 dBm or when C/I is under 10 dB.

There are also some other points where the performance of link adaptation can be

improved, especially in downlink: with reasonably good link quality, at RX-level -88 – -

90 dBm or at C/I values 18 – 25 dB the link adaptation uses MCS-9 although MCS-8

would offer better performance. This behavior is not severe: it just reduces the

performance slightly in the above-mentioned conditions. Nevertheless, it’s sensible to try

to optimize the performance in these conditions as well.

8.2. Optimization of Link Adaptation

Optimization of link adaptation was done by adjusting the modulation selection, MCS

selection and 8-PSK<->GMSK conversion look-up tables. Especially the modulation

selection table needed some modifications because the current link adaptation was often

unable to change to GMSK modulation even if the link quality was poor. Also some

minor modifications were done to the 8-PSK MCS selection table and GMSK MCS

selection table. All the modifications were done in order to optimize data throughput.

A number of BSC software test packets were created as candidates for the optimized link

adaptation algorithm. These different packages were tested to see which of the test

packets offered the best performance improvement compared to the original link

adaptation implementation. The different test packets were done with different approach:

some were more conservative, changing to lower MCSs earlier than the original LA

(when the link quality gets worse) and some tried to find the optimal performance level

with only small changes to the system. This kind of approach with many different test

packets was needed because at that point we knew that the changes were needed but we

were not able to say how big the changes had to be. After some measurements with the

test packets we were able to say which approach was the best for maximizing the

performance of link adaptation.


49

In the first LA software test packets the modulation change to GMSK was tried to be

made earlier (when the link quality decreases) than with the original LA by modifying the

values in the modulation selection table. The most conservative LA version (the 1st

version of the optimized LA, referred later in this thesis as Optimized LA1) offered the

best performance but the behavior of that link adaptation version was not, however,

optimal. The improvement in performance was minor although significant modifications

were made to the modulation table.

The downlink performance of Optimized LA1 with variable C/I scenario is presented in

Figure 30 and compared to the performance of the original link adaptation. In the

downlink data transfer the throughput performance of Optimized LA1 was better than the

throughput performance of the original LA but nevertheless the optimized version was

not able to change to GMSK modulation at the right moment. The throughput was

deteriorated to zero when C/I was 9 dB. Then when the link quality got worse, the

Optimized LA1 was able to change to GMSK and the data transfer continued properly.

The uplink performance of Optimized LA1 with variable C/I scenario is presented in

Figure 31 and compared to the performance of the original LA. In the uplink data transfer

the difference in performance between the Optimized LA1 and the original LA was

minor. The throughput with optimized LA was only slightly better in low C/I-values (C/I

< 10 dB) than the throughput with the original LA. The gap to the optimal level

(performance of most suitable MCS) was still rather large.

Figure 30. Downlink throughput performance of optimized link adaptation version 1

DL Throughput, C/I, 4 TSLs

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25 30 35

C/I (dB)

Thro

ughput (r

ela

tive)

Original LA

Optimized LA1

Optimal LA


modulation early enough


50

Figure 31. Uplink throughput performance of optimized link adaptation version 1

When investigating why the modifications of the modulation selection table were not

improving the performance as intended, it was discovered that also the GMSK<->8PSK-

conversion table needed to be modified so that the values of the conversion table would

correspond to the values of the modulation selection table. Since the values didn’t

correspond to each other with the Optimized LA1, the modulation was not always

changed to GMSK early enough. In addition, it was realized that near the modulation

change point GMSK and 8-PSK were used alternately even though the radio conditions

didn’t change. When GMSK modulation was used and the BEP estimates for 8-PSK were

unrealistic high (as with Optimized LA1), the modulation was changed to 8-PSK (blue

arrows in Figure 32, left side). When 8-PSK was in use and GMSK BEP values were

measured, the modulation was changed back to GMSK (because no conversion table was

needed). This led to so-called “ping-pong”-effect and the usage of 8-PSK modulation at

the circumstances where it should not have been used, ruined the performance. Figure 32

illustrates this behavior (optimized modulation selection table and non-optimized

conversion tables).

UL Throughput, C/I, 2 TSL

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25 30 35

C/I (dB)

Thro

ughput (r

ela

tive)

Original LA

Optimized LA1

Optimal LA


modulation


51

Figure 32. Modulation selection and GMSK/8-PSK BEP values with optimized modulation

selection table and non-optimized/optimized conversion table

New link adaptation versions were then created with modified conversion table values.

The new values for the conversion table were defined by measuring the GMSK BEP and

8-PSK BEP values in the laboratory conditions with variable RX-level and variable C/I

(configurations are explained in Chapter 7.2). It was also checked that the values of the

conversion table were corresponding to the values of modulation selection table to avoid

any “ping-pong”-effects as seen in Figure 32.

Now with the modified GMSK<->8-PSK conversion table the performance and behavior

of link adaptation was as it was intended (in Figure 32; optimized modulation and

conversion tables). The results of the measurements with final optimized link adaptation

are presented in the next chapter.

8.3. Measurement Results with Optimized Values

The measurement results with final optimized link adaptation are reviewed in this chapter

and compared to the baseline results. The measurements were executed using the same

configurations as with the baseline measurements. Only the link adaptation was changed

to the best optimized version (the 11th version of optimized LA, referred later in this

thesis as Optimized LA11).

Several MSs were used in these tests because different MSs have different radio

performance. That obviously affects the behavior of link adaptation. Especially a MS

feature called SAIC (Single-antenna interference cancellation) has noticeable influence

on performance. SAIC is a 3GPP specified feature that is able to cancel the impact of

GMSK BEP

8-PSK BEP

C/I, RX-level

BEP

8-PSK used GMSK

used

Desired change of

modulation

Change of modulation in practice

due to unrealistic conversion table

Measured BEP value:

8-PSK or GMSK BEP

GMSK BEP-> 8-PSK BEP

conversions

GMSK and 8-PSK used alternately

GMSK BEP

8-PSK BEP

C/I, RX-level

BEP

8-PSK used GMSK

used

Change of

modulation

Measured BEP value:

8-PSK or GMSK BEP

GMSK BEP-> 8-PSK BEP

conversions

Optimized modulation selection

and conversion tables Optimized modulation selection table

and non-optimized conversion tables


52

interference at the receiver. The cancellation works only for GMSK-modulation [28] and

that may cause problems for LA as GMSK quality is improved but 8-PSK quality isn’t.

The experience from the measurements was completely opposite, however: SAIC MSs

performed better with the optimized LA than non-SAIC ones.

Performance comparison of the link adaptation throughput measurement results is done

by calculating an integral (i.e the area under throughput measurement graph) over the

measured range for both original and optimized LA versions. Performance improvement

on used range is then calculated by comparing the results of the integrals. In variable RX-

level and fading scenarios the range where link adaptation performance is compared is

between RX-levels -110 – -75 dBm. In variable C/I scenario the comparison range is

between C/I-values 0 – 30 dB.

8.3.1. Measurements in Variable RX-level Scenario

In downlink throughput measurements in the variable RX-level scenario the optimized

link adaptation performed better than the original LA but with some older MSs (e.g.

Nokia 7270) the change of modulation from 8-PSK to GMSK was not optimal. This

caused 2 dB wide area where throughput deteriorated completely, around RX-level -102

dBm. This behavior was not seen with newer MSs (e.g. Nokia 6280). With new MSs

downlink performance of the link adaptation was close to the optimal performance level

with average improvement of +7% in whole range (-110 dBm – -75 dBm). The respective

performance improvement with older MSs was around +5%. Actually when link

adaptation was enabled the throughput performance in certain areas (RX-level -97 dBm –

-95 dBm) was even better than with the best fixed MCS. Downlink coverage for EGPRS

service was improved by 4 dB. Downlink throughput performance of the optimized link

adaptation in variable RX-level scenario is presented in Figure 33.


53

DL Throughput, variable RX-Level, 4 TSLs

0%

20%

40%

60%

80%

100%

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)

Throughput (relative)

Original LA

Optimized LA11 6280

Optimized LA11 7270

Optimal LA

Figure 33. Downlink FTP throughput in variable RX-level scenario

In uplink throughput measurements in variable RX-level scenario the optimized link

adaptation was working at optimal level with all MSs. Like in DL measurements in

certain area (around RX-level -88 dBm) the optimized LA was performing better than the

best fixed MCS. Performance improvement to the original link adaptation is clear:

average improvement of +17 % in whole range. Uplink coverage for EGPRS service was

improved by 5 dB. Uplink throughput performance of the optimized link adaptation in

variable RX-level scenario is presented in Figure 34.

UL Throughput, variable RX-Level, 2 TSL

0%

20%

40%

60%

80%

100%

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)


Original LA

Optimized LA11

Optimal LA

Figure 34. Uplink FTP throughput in variable RX-level scenario

RTT performance was also improved with the optimized link adaptation. Figure 35

presents the RTT measurement results made by using Ping packet size of 256 bytes in the

variable RX-level scenario. The improvement in performance was noticeable, though the


54

performance was not on the optimum level. Behavior of RTT with 32 byte- and 1460

byte-sized Ping packets was quite similar to 256 byte-sized one. There were some

differences in performance between MSs. The MS used in Figure 35 is Nokia 6280.

256B RTT, variable RX-level

0%

50%

100%

150%

200%

250%

300%

350%

400%

450%

500%

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-level (dBm)

RTT (relative)

Original LA

Optimized LA11

Figure 35. RTT with 256-byte-sized ping packet in variable RX-level scenario with Nokia 6280

Also in HTTP download measurements with 100 kB-html-page in variable RX-level

scenario there is clear performance improvement with the optimized link adaptation. As

with the original link adaptation web-page download time was ca. 60 seconds at -95 dBm

RX-level, the optimized link adaptation was able to perform the download even at RX-

level -102 dBm in ca. 35 seconds. HTTP download durations in variable RX-level

scenario with 100 kB-html page are presented in Figure 36.

100kB HTTP DL, variable RX-level

0.0

10.0

20.0

30.0

40.0

50.0

60.0

-70-75-80-85-90-95-100-102-104

RX-level (dBm)

Tim

e (s)

Original LA

Optimized LA11

Figure 36. HTTP download measurements with 100 kB-html-page in variable RX-level scenario

with Nokia 6280


55

8.3.2. Measurements in Variable C/I Scenario

In downlink measurements in variable C/I scenario the performance of the optimized link

adaptation was quite similar to the performance in variable RX-level scenario. Also in

variable C/I scenario there are differences in downlink performance among different

phones. New MSs achieved close to optimum performance level whereas older MSs

didn’t behave optimally when the modulation was changed. With variable C/I scenario

and with optimized link adaptation the area where DL throughput deteriorated completely

was 1 dB wide, at C/I-levels 9 – 10 dB, for older MSs. The respective area with the

original LA was much wider, 4-5 dB. The performance improvement of the optimized

link adaptation is +15 % for downlink with new MSs. The respective performance

improvement with older MSs was +13%. Downlink throughput performance of the

optimized link adaptation with variable C/I scenario is presented in Figure 37.

DL Throughput, C/I, 4 TSLs

0%

20%

40%

60%

80%

100%

0 5 10 15 20 25 30 35

C/I (dB)


Original LA

Optimized LA11 6280

Optimized LA11 7270

Optimal LA

Figure 37. Downlink throughput performance with variable interference (in DL)

In uplink measurements in variable C/I scenario the performance improvement of the

optimized link adaptation is not as big as the respective improvement in variable RX-

level scenario. This is due to the fact that the change of modulation is done earlier than

necessary when link quality decreases. Therefore the performance of optimized LA is

below the performance of the original LA between C/I-ratios 10 – 15 dBm. The behavior

of the optimized LA is very stable (data throughput continues down to C/I value of 0 dB)

when compared to the original link adaptation. Performance improvement in uplink is

+3%. Uplink throughput performance of the optimized link adaptation with variable C/I

scenario is presented in Figure 38.


56

UL Throughput, C/I, 2 TSL

0%

20%

40%

60%

80%

100%

0 5 10 15 20 25 30 35

C/I (dB)

Thro

ughput (relative)

Original LA

Optimized LA11

Optimal LA

Figure 38. Uplink throughput performance with variable interference (in UL)

RTT performance of the optimized link adaptation is at the optimal level throughout the

whole range. There are some differences in performance depending on the used MS but

generally the performance improvement is bigger in variable C/I scenario than in the

variable RX-level scenario. RTTs with all different Ping packet sizes (32B, 256B, 1460B)

behave in the same way. RTT performance of the optimized link adaptation with 256

byte-sized Ping packet in variable C/I scenario is presented in Figure 39.

256B RTT, C/I in DL

0%

50%

100%

150%

200%

250%

300%

350%

400%

450%

500%

0 5 10 15 20 25

C/I (dB)

RTT (relative)

Original LA

Optimized LA11

Figure 39. RTT with 256-byte-sized ping packet in variable C/I scenario (interference in

downlink) with Nokia 6280


57

HTTP download measurements with 100 kB-html page also show a clear improvement

when the performance of the optimized link adaptation is compared with the performance

of the original LA in the variable C/I scenario. As with the original link adaptation it is

not possible to download the web-page when C/I is lower than 8 dB, the optimized link

adaptation enables downloads down to C/I = 0 dB in ca. 25 seconds time. HTTP

download durations in variable C/I scenario with 100 kB-html page are presented in

Figure 40.

100kB HTTP DL, C/I

0.0

10.0

20.0

30.0

40.0

50.0

60.0

3020151310986420

C/I (dB)

Tim

e (s)

Original LA

Optimized LA11

Figure 40. 100 kB-html page download performance over HTTP in variable C/I scenario

(interference in downlink) with Nokia 6280

8.3.3. Measurements in Fading Scenario

Based on the measurements made in downlink fading scenario the optimized link

adaptation is working very near the optimum level. The 1-2 dB wide areas (where

throughput deteriorated completely) that could be seen with older MSs on static

laboratory measurements were not seen in the fading scenario. As the signal quality is not

static, the quality is not poor all the time and the forward error correction and IR

procedures of EGPRS are able to provide some throughput for the user even if the radio

conditions are rather poor in average. Therefore the end-to-end throughput does not

deteriorate totally as happened in more static radio conditions.

In TU3 environment the downlink performance of the optimized LA is at the optimal

level almost throughout the range. On the point where modulation is changed the

performance of the optimized LA is 5% lower than the optimum level. With TU3 fading

the performance improvement on downlink with respect to the original link adaptation is

+4 % and coverage for EGPRS service is improved by 2 dB. Downlink throughput


58

performance of the optimized link adaptation with TU3 fading scenario is presented in

Figure 41.

DL Throughput, TU3 Fading. 4 TSLs

0%

20%

40%

60%

80%

100%

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)

Thro

ughput (relative)

Original LA

Optimized LA11

Optimal LA

Figure 41. Downlink throughput performance with TU3 fading and variable RX-level

In TU50 environment the downlink throughput performance is improved at low RX-

levels when comparing to the original link adaptation. With high RX-levels (RX > -85)

the performance is slightly reduced compared to the original LA. This is probably due to

the more conservative selection of codecs. This really pays off with low RX-levels where

performance is improved. With TU50 fading performance improvement with respect to

the original LA is +2% and coverage for EGPRS service is improved by 6 dB. Downlink

throughput performance of the optimized link adaptation with TU50 fading scenario is

presented in Figure 42.

DL Throughput, TU50 Fading, 4 TSLs

0%

20%

40%

60%

80%

100%

-110 -105 -100 -95 -90 -85 -80 -75 -70

RX-Level (dBm)

Thro

ughput (relative)

Original LA

Optimized LA11

Optimal LA

Figure 42. Downlink throughput performance with TU50 fading and variable RX-level


59

8.3.4. Measurements in Live Network

Measurements in live network were executed in Ruoholahti as explained in Chapter 7.3.

The defined route was driven four times for downlink data transfer measurements and

two times for uplink data transfer measurements with the original and the optimized link

adaptation. RX-levels on the route were between -65 and -105 dBm, average RX-level

being -80 dBm. Average C/I was 25 dB. The BTS used in the live network was Nokia

UltraSite in 1800-MHz band. In Figure 43 there’s a summary of application level

throughput averages for both downlink and uplink. The optimized link adaptation

improved the performance for both directions: there was +11% improvement achieved in

the downlink throughput and +31% improvement achieved in the uplink throughput.

Scaling of the results was done using maximum downlink throughput level in laboratory

as a reference level.

FTP Throughput average in live-network during driving test

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FTP 2 MB DL FTP 1 MB UL


Original LA

Optimized LA11

Figure 43. FTP average throughput during driving tests

On the entire route the optimized link adaptation seemed to be working more stable than

the original LA which resulted in higher overall downlink throughput. Figures 44 and 45

show downlink throughput performance along the driven route. A map with the route is

presented in Figure 15. The biggest difference between the original and the optimized LA

was on the western part of the route where RX-level was between -85 and -105 dBm.

There the optimized LA was much more stable and therefore was able to offer better

throughput than the original LA. Throughput measurement was made by downloading a 2

MB file using FTP application. As the download of the file was complete, the same file

was downloaded once again. This caused some breaks in transfer when one download had

ended and the next one was to be started. These breaks can be seen in Figures 44 and 45


60

as individual black lines on the spots where the throughput on the other rounds has been

on a high level.

Figure 44. Downlink throughput during driving test with the original link adaptation

Figure 45. Downlink throughput during driving test with the optimized link adaptation

Figure 46 presents a more detailed view on the western part of the route by showing

retransmission rate along the route. The retransmission rate with the optimized LA has

decreased when comparing it with the retransmission rate that was observed with the

original LA. This is caused by more conservative selection of coding schemes. Since the

retransmission rate is lower, it seems that the optimized solution is choosing more robust

codecs than the original LA when link quality is poor.


61

Figure 46. Number of retransmissions during DL data transfer at low RX-levels

If we want to see a more detailed view on the behavior of link adaptation, we have to

compare throughput performance at certain places on the route. Figure 47 shows RLC

throughput in downlink on the western part of the route (same part as in Figure 46). All

RLC throughput comparisons in this thesis are taken exactly from the same parts of the

route for both original and optimized solutions to see the changes in link adaptation

behavior reliably. In the western part the optimized link adaptation was working more

stable than the original LA as link quality got worse. No such drops in RLC throughput

were seen as observed with the original link adaptation. Also when link quality started to

get better, the optimized solution was able to continue data transfer much earlier than the

original one.

Figure 47. RLC downlink throughput (on Y-axis) as a function of time (on X-axis) at low RX-

levels (same part of the route as in Figure 45)

Original link adaptation

Optimized link adaptation

RX-level

RX-level

Original link adaptation Optimized link adaptation


62

Figure 48 shows the downlink throughput performance on the southern part of the route.

RX-levels on this part of the route are between -70 dBm and -88 dBm. With these RX-

levels the original link adaptation used too much MCS-9 and this caused drops in

throughput. As the optimized link adaptation switched earlier to MCS-8 from MCS-9

when the RX-level got lower, the throughput was better than with the original LA. The

big wide drops in Figure 48 were caused by breaks between downloaded files.

Figure 48. RLC downlink throughput (on Y-axis) as a function of time (on X-axis) during southern

part of the route

On uplink data transfer the improvement in performance of the optimized link adaptation

can be seen even more clearly than in downlink. Figures 49 and 50 show uplink

throughput performance along the route. The route is exactly the same as in downlink

measurements. As RX-level on the MS side is -70 – -105 dBm, the RX-level on BTS side

is lower due to the smaller transmit power of the MS. This means that uplink conditions

in the same environment are more challenging than downlink conditions. That is the

reason for bigger performance improvement (+35%) than in downlink measurements

(+11%). Throughput with the optimized link adaptation was better than the throughput

with the original LA almost everywhere on the route. Especially on the western and

southern loops of the route the improvement was significant.

RX-level

RX-level




63

Figure 49. Uplink throughput during driving test with the original link adaptation

Figure 50. Uplink throughput during driving test with the optimized link adaptation

If we analyze uplink throughput on certain parts of the route, the same improvement can

be seen in more detailed way. Figure 51 shows uplink RLC throughput on the same part

of the route as shown in Figure 47 (western part). Performance of the optimized link

adaptation was better than the performance of the original LA all the time. The optimized

version was able to continue data transfer throughout the challenging part of the route

whereas throughput with the original LA stalled several times.

Improved performance on uplink data transfer is due to the same reason as in downlink:

more conservative selection of MCSs. This can be seen in Figure 52 where the used


64

MCSs are shown for the same part of the route as shown in Figure 51. With optimized

solution the usage of GMSK codecs was higher and the selection of the MCSs was more

stable than with the original LA. With the original LA big changes in MCS selection were

more common (e.g. MCS6->MCS3).

Figure 51. RLC uplink throughput (on Y-axis) as a function of time (on X-axis) during low RX-

levels (same part of the route as in fig. 46)

Figure 52. Used MCS (on Y-axis) as a function of time (on X-axis) in UL during low RX-levels

(as in fig. 50)

RX-level

RX-level





RX-level

RX-level


65

Uplink throughput with a reasonably good link quality is also improved greatly with the

optimized link adaptation. Figure 53 shows uplink throughput performance on the

southern part of the route. The optimized LA was using mainly MCS-7 and MCS-8 on

that part of the route. The original LA was using in addition to MCS-7 and MCS-8, also

MCS-9. That had negative impact on uplink performance as MCS-9 was not robust

enough to successfully continue data transfer. This caused serious drops to throughput.

Figure 53. RLC uplink throughput (on Y-axis) as a function of time (on X-axis) during southern

part of the route

RX-level

RX-level




66

9. Results of the Optimization

In this chapter the results of the link adaptation optimization are summarized.

Performance of the optimized solution is analyzed separately for tests in laboratory

environments and live network. Reason for this is that with laboratory measurements we

are able to see the behavior of the optimized LA in more detail and we can analyze better

the performance compared to the optimal level. Measurements in live network, on the

other hand, are needed to verify that the gain seen in laboratory measurements is also

visible in real radio environment.

Measurements done with the optimized link adaptation offered encouraging results. The

optimized LA was improving performance when compared to the original LA in all cases.

The performance was very near or at the optimum level with the optimized version

almost in all cases. Still there are some situations where the performance of the optimized

LA could be improved. Summary of performance improvements with the optimized link

adaptation is presented in Table 6.

Table 6. Summary of performance improvement with the optimized link adaptation

Laboratory measurements

Throughput improvement

Coverage improvement



RX-level DL +7% +4 dB UL +17% +5 dB

C/I DL +15% +1 dB UL +3% +6 dB

Live Measurements





drive route DL +11% <not

measured> UL +31% <not

measured>

9.1. Performance in Laboratory Environment

9.1.1. Downlink Performance

In laboratory conditions downlink throughput performance with the optimized link

adaptation was improved in average by +12 % in the whole range of the cell. The

improvement in RTT and html-page download measurements was also very clear.

Coverage where EGPRS data transfer can be used was improved by +4 dB. Performance

of the optimized link adaptation was near the optimum level almost in all cases with and

without fading.


67

In laboratory measurements several MSs from different generations were used. This was

very helpful as different MSs had different receiver capabilities and that had effect also

on the behavior of link adaptation. New MSs were working at optimal level in all cases

with the optimized LA in downlink direction. With some older MSs there were still some

problems after the optimization when changing modulation. This caused 1-2 dB wide area

where throughput deteriorated completely. In that area, GMSK-modulation should have

been selected instead of 8-PSK-modulation. This behavior was seen in static

measurements in variable RX-level and variable C/I scenarios. In the measurements made

in fading scenario also these MSs were working optimally with the optimized LA.

The reason why certain MSs were not able to perform the change of modulation early

enough might be due to their receiver characteristic: their estimation for GMSK link

quality might be unrealistic. It was seen in the tests that the link quality with GMSK was

still at maximum level even if 8-PSK link quality was already so poor that no data could

be transferred with 8-PSK modulation. This caused problems with the current link

adaptation algorithm as the latest possible time to change to 8-PSK (as the link quality is

getting better) is when the GMSK quality reaches the maximum level (if we chose to use

GMSK even when the GMSK link quality was perfect, we would never be able to change

to 8-PSK modulation). With some MSs even this moment is too early and they try to use

8-PSK although it is not robust enough for data transfer in those conditions. Link

adaptation can try to change modulation back to GMSK based on the 8-PSK BEP values

but even then some transmissions are done with 8-PSK. This is not enough for data

transfer to continue in certain (max. 2 dB wide) areas as seen in Figures 33 and 37. This

behavior is illustrated in Figure 54. Despite the non-optimal behavior on the modulation

selection the downlink performance with the optimized LA is improved almost as much

as with newer MSs when comparing to the original LA.

Figure 54. Selection of modulation with same link adaptation version and different MSs

GMSK BEP

8-PSK BEP

C/I, RX-level

BEP

8-PSK used GMSK

used

Change of modulation in

practice

Measured BEP value: 8-

PSK or GMSK BEP

GMSK BEP

8-PSK BEP

C/I, RX-level

BEP

8-PSK used GMSK

used

Desired change of

modulation

Change of modulation in

practice

Measured BEP value:

8-PSK or GMSK BEP

GMSK BEP decreases later

New MSs (Rel’04+SAIC) Older MSs (Rel’04+non-SAIC)

GMSK and 8-PSK used alternately


68

9.1.2. Uplink Performance

In laboratory environment uplink throughput performance with the optimized link

adaptation was improved in average by +9% in the whole range of the cell. The behavior

of the optimized link adaptation on uplink was very near the optimal level with all MSs.

The MSs that were not working optimally when the modulation was changed on

downlink were working correctly on uplink direction. The EGPRS coverage in uplink

direction was improved by +5 dB.

The only measurement where optimized LA was not working optimally in UL direction

was the one made in variable C/I scenario. There modulation was changed too early

(when the link quality decreased) to GMSK reducing the performance slightly (Figure

38). In variable RX-level scenario the change of modulation was done exactly in the right

spot and therefore it would make no sense to adjust the link adaptation only for C/I uplink

conditions. If the change of modulation is too early, that doesn’t cause any problems, just

slight decrease in performance. If the change is too late, that can ruin the performance

completely on a certain area.

9.2. Performance in Live Network

In live network the performance improvement can be as clearly seen as in laboratory

conditions. The live measurements were done as drive tests and RX-levels during the

driven route represented well the whole range of the cell: -65 dBm – -105 dBm.

Downlink TCP data throughput during drive tests was improved by +11% and uplink

TCP data throughput by +31%. In downlink direction the biggest improvement on the test

route was observed when link quality was poor. In uplink data transfer the throughput

was improved on almost every part of the route. Also retransmission rate and BLER were

both reduced with the optimized LA.

The behavior of the optimized link adaptation was much more stable than the behavior of

the original LA. The differences in the behavior could be seen particularly in low RX-

levels (-85 – -105 dBm) but also with reasonably good link quality (RX-levels: -70 – -85

dBm): RLC throughput was much more stable resulting in also higher TCP throughput.

Behavior of the optimized link adaptation was very similar in laboratory and live

environment. In live network it seems that the optimized LA is able to improve

performance even more than in laboratory environment. This proves that even if the LA


69

optimization work was done in laboratory, the results improve the system performance

also in real networks.

9.3. Further Study Items and Future Improvement

Potential

The results achieved in this thesis are well in accordance with the original objectives. The

main objective was to get link adaptation to operate at ideal level. This was achieved as

the optimized LA is able to use most suitable coding schemes in almost all cases. This

leads to more stable RLC throughput which results in noticeable improvements also on

application level performance.

To be certain that the performance level obtained in this thesis can be reached in all

environments and conditions some further studies should be carried out. Link adaptation

performance should be tested with more MS types as the transceiver performance of MS

has great effect on the LA performance. Also the effect of certain GSM features on LA

(such as frequency hopping) should be analyzed. Analyses in commercial operators’

networks would offer valuable information on the performance of link adaptation in real

environment. The analysis could be carried out by using Key Performance Indicator

(KPI) data from Network Management Subsystem.

After the optimization work there was still some room for improvements. Biggest

improvement potential of the optimized link adaptation is in downlink data transfer with

some older MSs. If we wanted to optimize the system performance further from the link

adaptation point of view, the LA algorithm should be improved e.g. by introducing new

inputs to the algorithm. If RX-level and C/I could be used as criteria when choosing the

modulation, the behavior illustrated in Figure 54 wouldn’t be a problem. The modulation

could be changed earlier to GMSK (when link quality decreases) based on low RX-level

or low C/I ratio. That would prevent the drops in performance with all MSs.

This enhanced algorithm would improve the performance with certain MSs on downlink

but then on the other hand, the performance which is now at the optimum level might go

down in some cases because of too early change to GMSK modulation.


70

10. Conclusions

The scope of this thesis was to improve the performance of EGPRS link adaptation. The

optimization work was done with real equipment in laboratory and in live network

environments to maximize the performance improvement in real networks.

First the baseline measurements were executed with the original system to see the areas

where the performance was not optimal. These areas were then thoroughly analyzed to be

able to understand how the system performance could be improved. The changes to the

link adaptation were implemented according to these analyses. Various versions of link

adaptation were created and tested to see which offered the best performance and if the

changes were working as intended. After every new version we were able to reduce the

gap between the implemented and ideal link adaptation.

The final version of the optimized link adaptation was working at the optimum level in

almost all cases. The performance improvement to the original link adaptation could be

clearly seen in laboratory and live network. In laboratory the throughput performance was

improved by +11% in average. Coverage for EGPRS service was improved by 1-6 dB

depending on circumstances. In live network throughput improvement was +11% and

+31% in downlink and in uplink data transfer, respectively.

Although the results with the optimized link adaptation were optimal in almost every

environment there was still room left for improvement with certain MSs. To be able to

meet the optimum performance level with all mobile stations the link adaptation

algorithm could be enhanced further for example by introducing new inputs for LA

algorithm.


71

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to Rel’4)”; GSM, GPRS and EDGE Performance, Chapter 1, On pages: 3-53, John Wiley & Sons, Ltd.

[3] 3GPP TS 45.001 version 4.5.0 Release 4 (2005); “Physical layer on the radio

path; General description”; Annex A “Reference Configuration”.

[4] Molkdar D., Featherstone W., Larnbotharan, S. (2002) “An Overview of EGPRS:

The Packet Data Component of EDGE”; Electronics & Communication

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[9] Gomez G., Sanchez R., Cuny R., Kuure P., Paavonen T. (2003) “Packet Data

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[10] Nanda S., Balachandran K., Kumar, S. (2000); ”Adaptation Techniques in

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[11] Lee D.S., Lin C.C. (2002); “Window adaptive TCP for EGPRS networks”; The

5th International Symposium on Wireless Personal Multimedia Communications,

Volume 2, On pages: 853- 857.

[12] Sánchez R., Martinez J., Romero J., Järvelä R. (2002); “TCP/IP Performance

over EGPRS network” Vehicular Technology Conference (VTC) 2002-Fall,

Volume 2, On pages: 1120-1124.

[13] Huang D., Shi J.J. (2000); ”TCP over packet radio”; Emerging Technologies Symposium: Broadband, Wireless Internet Access, IEEE

[14] Propsim C8 Operation Manual (2003); “Channel Modeling Theory”; Chapter 8


72

[15] Romero J., Martinez J., Nikkarinen S., Moisio M. (2003) ; “GPRS and EGPRS

Performance”; GSM, GPRS and EDGE Performance (Second Edition), Halonen

T, Romero J., Melero J., Chapter 7, On pages: 235-305, John Wiley & Sons, Ltd.

[16] Featherstone W., Molkdar D. (2001); “Impact of Imperfect Link Adaptation in

EGPRS”; 3G Mobile Communication Technologies, Second International Conference, Conf. Publ. No. 477, On pages: 277-281.

[17] Ericsson White Paper (2003); “EDGE, Introduction of high-speed data in

GSM/GPRS networks”; www.ericsson.com/technology/whitepapers/edge_wp_technical.pdf

[18] 3GPP TS 44.060 version 4.23.0 Release 4 (2005); “Radio Link Control/Medium

Access Control protocol”; Chapter 8.1, Tables 8.1.1.1. and 8.1.1.2.

[19] Featherstone W., Molkdar D. (2000); “System Level Performance Evaluation of

EGPRS in GSM Macro-cell Environments”; Vehicular Technology Conference

(VTC) 2000-Fall, Volume 6, On pages: 2653-2660.

[20] 3GPP TS 45.008 version 4.17.0 Release 4 (2005); “Radio subsystem link

control”; Annex D, Table 3.

[21] Propsim fading simulator: http://www.propsim.com

[22] 3GPP TS 45.005 version 4.18.0 Release 4 (2005); ”Radio transmission and reception”; C3.3 Typical Urban (TU) propagation model on page 79.

[23] Link Adaptation training material (2005); “Link Adaptation - Introduction”;

Nokia Internal document

[24] Pirhonen R., Salmenkaita M. (2002); “Link Performance Enhancements”; GSM,

GPRS and EDGE Performance, Halonen T, Romero J., Melero J., Chapter 10, On

pages: 343-362, John Wiley & Sons, Ltd.

[25] Nemo Outdoor drive test tool: http://www.nemotechnologies.com

[26] Microsoft Internet Explorer: http://www.microsoft.com/windows/ie

[27] Heliste H. (2003); “EGPRS Uplink Link Adaptation Challenge”; Nokia Internal document.

[28] Kobylinski R., Ghosh A., Mostafa A. , Whitehead J. (2005); “EDGE terminal

with interference cancellation and spatial diversity processing”; International Conference on Wireless Networks, Communications and Mobile Computing;

Volume 2, On pages: 884- 889.


73

Appendix A:

3GPP TS 45.005

Typical Urban (TU) 6-tap propagation model, variant 1 [22]

Tap number Relative time (µs)

Average relative

power (dB)

Doppler

spectrum

1 0,0 -3 Classical

2 0,2 0 Classical

3 0,5 -2 Classical

4 1,6 -6 Classical

5 2,3 -8 Classical

6 5,0 -10 Classical

3GPP TUx Propagation Model

-40

-30

-20

-10

0

-1 0 1 2 3 4 5 6

Delay [us]

Strength (dB)


74

Appendix B:

3GPP TS 45.002 version 4.8.0 Release 4

MS classes for multislot capability

Multislot Maximum number of slots

class Rx Tx Sum

1 1 1 2

2 2 1 3

3 2 2 3

4 3 1 4

5 2 2 4

6 3 2 4

7 3 3 4

8 4 1 5

9 3 2 5

10 4 2 5

11 4 3 5

12 4 4 5

13 3 3 NA

14 4 4 NA

15 5 5 NA

16 6 6 NA

17 7 7 NA

18 8 8 NA

19 6 2 NA

20 6 3 NA

21 6 4 NA

22 6 4 NA

23 6 6 NA

24 8 2 NA

25 8 3 NA

26 8 4 NA

27 8 4 NA

28 8 6 NA

29 8 8 NA


75

Appendix C:

Reliability of the measurement results

The measurements for this thesis were done with quite a low number of samples per one

measurement. This was mainly due to the fact that the measurements were time-

consuming and the number of different kinds of measurements was large. If test

automation could have been used, the number of samples could have been much higher.

Now the measurements were done with only 3-5 samples per one measurement.

Therefore it’s not possible to prove the statistical reliability of the results. By analyzing

the results it can be seen that in practice the results should present quite reliably the real

performance of the system.

Here UL throughput measurement results are analyzed as an example of the measurement

results. Figure C1 presents all the samples from UL throughput measurement in variable

RX-level scenario. The same measurement values are presented also in Table C1. In this

measurement 3 samples per RX-level and per link adaptation version were measured.

It can be clearly seen in Figure C1 that the results of different samples (in same RX-level

and with same LA version) don’t differ essentially. There is some deviation between the

samples but in all cases all samples of one link adaptation version are clearly

differentiated from the respective samples of other LA version if there is some difference

in average value. The same kind of behavior can be seen in all measurements.

Although the absolute difference between the performance of the different link adaptation

versions can’t be precisely determined with such a low number of samples, the overall

improvement of optimized link adaptation in certain areas (in this measurement when

RX-level < -90 dBm) can be clearly seen and can be considered as reliable.


76

UL Throughput, Variable RX-level, 2 TSL

0%

20%

40%

60%

80%

100%

120%

-110 -105 -100 -95 -90 -85 -80 -75 -70 -65

RX-Level (dBm)


Original LA meas. 1 Original LA meas. 2 Original LA meas. 3Optimized LA11 meas. 1 Optimized LA11 meas. 3 Optimized LA11 meas. 3Average of Original LA Average of Optimal LA11

Figure C1: Uplink FTP throughput measurement in variable RX-level scenario with all measured

samples

Table C1: Uplink FTP throughput measurement values (relative to maximum throughput) in

variable RX-level scenario

RX-level (dBm) O

riginal LA

meas. 1

Original LA

meas. 2

Original LA

meas. 3

Average of

Original LA

Optimized

LA11

meas.1

Optimized

LA11

meas.2

Optimized

LA11

meas.3

Average of

Optimized

LA11

-104 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

-102 0.0% 0.0% 0.0% 0.0% 7.2% 6.5% 9.0% 7.6%

-100 0.0% 0.0% 0.0% 0.0% 16.8% 16.6% 14.2% 15.9%

-97 3.4% 2.5% 3.0% 3.0% 23.2% 23.5% 22.1% 22.9%

-95 12.3% 7.8% 7.8% 9.3% 25.6% 23.8% 26.6% 25.3%

-92 18.6% 19.2% 18.8% 18.9% 38.3% 38.9% 37.6% 38.3%

-90 49.8% 50.7% 50.3% 50.3% 50.7% 52.1% 51.1% 51.3%

-88 51.3% 50.2% 50.8% 50.8% 60.1% 64.7% 63.4% 62.7%

-85 75.6% 78.6% 78.4% 77.5% 78.1% 76.6% 77.1% 77.3%

-80 98.3% 96.3% 96.9% 97.2% 97.9% 99.4% 98.4% 98.6%

-75 100.1% 100.3% 98.4% 99.6% 99.2% 98.4% 98.7% 98.8%

-70 98.6% 99.8% 100.2% 99.5% 99.4% 99.3% 98.5% 99.1%


77

Company Confidential Appendix D:

Specification for Modulation and MCS-Selection Tables of EGPRS Link Adaptation

Final optimized LA (version LA11)

→ Relationship of GMSK and 8PSK BEP is changed (Table 12 in EGPRS IS)

→ Modulation selection table is changed (Table 13 in EGPRS IS) → MCS selection table for GMSK is changed (Table 14 in EGPRS IS)

→ MCS selection table for 8-PSK is changed (Table 15 in EGPRS IS)

New Table:

Reported

GMSK

MEAN_BEP

Estimation for

8-PSK

MEAN_BEP

Reported

8-PSK

MEAN_BEP

Estimation for

GMSK

MEAN_BEP

0 – 7 0 0 7

8 – 19 1 1 18

20 – 21 2 2 21

22 – 23 3 3 23

24 – 25 4 4 25

26 – 27 5 5 27

28 6 6 28

29 – 30 7 7 29

31 8 8 – 31 31

Table 12. Relationship of GMSK and 8PSK mean BEP.

Old Table:

Reported

GMSK

MEAN_BEP

Estimation for

8-PSK

MEAN_BEP

Reported

8-PSK

MEAN_BEP

Estimation for

GMSK

MEAN_BEP

0 – 7 0 0 3

8 – 9 1 1 8

10 – 11 2 2 10

12 – 13 3 3 12

14 – 15 4 4 14

16 – 18 5 5 17

19 – 20 6 6 19

21 – 23 7 7 22

24 – 25 8 8 24

26 – 28 9 9 27

29 – 30 10 10 29

31 11 11-31 31

Table 12. Relationship of GMSK and 8PSK mean BEP.


78

New table:

8PSK CV_BEP

8PSKMEAN_BEP

0 1 2 3 4 5 6 7

0 0 0 0 0 0 0 0 0

1 3 3 3 3 3 2 2 2

2 7 7 6 6 5 5 4 3

3 9 9 8 8 7 7 6 5

4 11 11 9 9 8 8 7 7

5 15 15 14 13 12 10 9 8

6 16 16 15 14 13 12 11 9

7 18 18 16 15 14 13 12 10

8 – 31 32 32 32 32 32 32 32 32

Table 13. GMSK mean BEP limits for modulation selection.

Old table:

8PSK CV_BEP

8PSKMEAN_BEP

0 1 2 3 4 5 6 7

0 0 0 0 0 0 0 0 0

1 6 6 6 6 6 6 5 5

2 9 9 9 9 9 9 7 6

3 32 32 32 32 21 12 11 8

4 32 32 32 32 32 20 13 12

5 32 32 32 32 32 24 21 21

6 – 31 32 32 32 32 32 32 32 32

Table 13. GMSK mean BEP limits for modulation selection.


79

New Table:

GMSK_CV_BEP

GMSK_MEAN_BEP

0 1 2 3 4 5 6 7

0 – 5 1 1 1 1 1 1 1 1

6 2 2 2 1 1 1 1 1

7 2 2 2 2 2 2 1 1

8 – 9 2 2 2 2 2 2 2 2

10 3 3 3 2 2 2 2 2

11 3 3 3 3 3 2 2 2

12 – 21 3 3 3 3 3 3 3 3

22 – 31 4 4 4 4 4 4 4 4

Table 14. MCS selection table for GMSK.

Old Table:

GMSK_CV_BEP

GMSK_MEAN_BEP

0 1 2 3 4 5 6 7

0 – 3 1 1 1 1 1 1 1 1

4 2 2 1 1 1 1 1 1

5 2 2 2 1 1 1 1 1

6 2 2 2 2 2 2 1 1

7 – 9 2 2 2 2 2 2 2 2

10 – 19 3 3 3 3 3 3 3 3

20 – 31 4 4 4 4 4 4 4 4

Table 14. MCS selection table for GMSK.


80

New Table:

8-PSK_CV_BEP

8-PSK_MEAN_BEP

0 1 2 3 4 5 6 7

0 – 3 5 5 5 5 5 5 5 5

4 6 5 5 5 5 5 5 5

5 6 6 5 5 5 5 5 5

6 6 6 6 5 5 5 5 5

7 6 6 6 5 5 5 5 5

8 6 6 6 6 5 5 5 5

9 6 6 6 6 6 5 5 5

10 – 16 6 6 6 6 6 6 6 6

17 – 21 7 7 7 7 7 7 7 7

22 – 28 8 8 8 8 8 8 8 8

29 – 31 9 9 9 9 9 9 9 9

Table15. MCS selection table for 8-PSK.

Old Table:

8-PSK_CV_BEP

8-PSK_MEAN_BEP

0 1 2 3 4 5 6 7

0 – 3 5 5 5 5 5 5 5 5

4 6 5 5 5 5 5 5 5

5 6 6 5 5 5 5 5 5

6 6 6 6 5 5 5 5 5

7 6 6 6 5 5 5 5 5

8 6 6 6 6 5 5 5 5

9 6 6 6 6 6 5 5 5

10 – 16 6 6 6 6 6 6 6 6

17 – 21 7 7 7 7 7 7 7 7

22 – 25 8 8 8 8 8 8 8 8

26 – 31 9 9 9 9 9 9 9 9

Table15. MCS selection table for 8-PSK.

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