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Rate and Power Adaptation Techniques for Wireless Communication Systems Rate and Power Adaptation Techniques for Wireless Communication Systems Thesis submitted to the University of Cardiff in candidature for the degree of Doctor of Philosophy Lay Teen Ong Centre of Digital Signal Processing Cardiff University 2007 UMI Number: U584941 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Dissertation Publishing UMI U584941 Published by ProQuest LLC 2013. Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 Declaration This work has not previously been accepted in substance for any degree and is not concurrently submitted in candidature for any degree. Signed ......................... (Candidate) Date 5 1 T.0 5 5 . 7 ° ? . Statement 1 This thesis is being submitted in partial fulfilment of the requirements for the degree of PhD. Signed .......................... (Candidate) Date 99? Statement 2 This thesis is the result on my own independent work/investigation, except where otherwise stated. Other sources are acknowledged by explicit references. Signed ...............................................(Candidate) Date Statement 3 I hereby give consent for my thesis, if accepted, to be available for photocopying and for inter-library loan, and for the title and summary to be available to outside organisations. Signed ................ *".£5....................... (Candidate) Date A bstract Attaining the most spectrally efficient form of data transmission over a time- varying channel remains as fundamentally important target in wireless systems. Link adaptation (LA) is a promising approach to increase spectral efficiency. In general, the transmitter adjusts its parameter such as rate, power and coding in accordance with the channel state information (CSI) fed back from the receiver. Consequently, the accuracy of the CSI is prevalent in LA design. In this thesis, an investigation of the performance of a variable rate variable power (VRVP) multi-level quadrature amplitude modulation (MQAM) scheme is performed for a single antenna system. Then, a novel VRVP-MQAM system is proposed that employs a rate and power adaptation algorithm based on the statistical charac­ terization of CSI imperfection. Instead of using the conventional signal-to-noise ratio (SNR) estimate as a CSI parameter, the proposed system is based on both an SNR estimate and a bit error rate (BER) estimate, as BER is a more direct representation for quality of service (QoS) of a communication system. The pro­ posed rate and power adaptation algorithm is then generalized to incorporate a pilot symbol assisted modulation (PSAM) based channel predictor. The BER and SNR estimates are then employed within a code division multiple access (CDMA) based rate and power adaptation system. Finally, the performances of the pro­ posed systems are shown to achieve higher spectral efficiency when compared to the alternative systems derived based on conventional approach. Another requirement in today’s wireless digital communication systems is to provide services for integrated voice and data traffic. The QoS requirement for voice and data can be application specific. For example, real-time traffic is delay- constrained, whereas non-real time traffic has a relaxed requirement on delay but may be capacity-constrained. With this motivation, a rate and power adaptation technique is proposed for a multiple-input multiple-output (MIMO) based inte­ grated voice and data service. On the basis of analytical and simulation results, the performance of the proposed scheme is assessed for a Rayleigh fading environ­ ment. Finally, the results demonstrated that the MIMO based system is suitable for integrate voice and data traffic with different requirements and specification. Acknowledgements I would like to thank my supervisors Dr. Sangarapillai Lambotharan and Pro­ fessor Jonathon A. Chambers at Cardiff University, and Dr. Mohammad Shikh- Bahaei at King’s College London. Without their continuous support and guid­ ance, I would not have completed my thesis. I also wish to thank all my friends at King’s College London and Cardiff Uni­ versity. Their presence has brightened up the research environments. A special thank also goes to Ms Theresa Burnette of King’s College London. Her profes­ sional advice has made my journey so much easier. Finally, I want to send my most heartfelt gratitude to my family. My husband, Yew Fei Tang, for his endless love, support, trust,..., a list without bound that is impossible to complete here. I also thank my parents Sem Yam and See An, for their understanding and bravery. This thesis is dedicated to them. iv C ontents 1 Introduction 1 1.1 Aims and Objectives ............................................................................... 5 1 .2 Thesis Outline ............................................................................................ 5 2 Channel Model 7 2.1 F a d in g ......................................................................................................... 7 2.2 Small Scale Fading and Multipath Effect .......................................... 7 2.3 Multipath Time Delay Spread: Flat/Frequency Selective Fading . 8 2.3.1 F la t-F a d in g .................................................................................... 8 2.3.2 Frequency Selective Fading ......................................................... 12 2.4 Doppler Spread: Fast/Slow Fading .................................................... 13 2.5 Summary .................................................................................................. 14 3 Link Adaptation Techniques under Perfect CSI Knowledge 16 3.1 In tro d u ctio n ............................................................................................... 16 3.2 Capacity of a Time-Varying C h a n n e l ................................................. 17 3.2.1 Optimal Rate and Power Adaptation ...................................... 17 3.2.2 Sub-Optimal Transmitter Adaptations .................................. 19 3.2.3 Numerical Results ...................................................................... 21 3.3 VRVP-MQAM S y s te m ........................................................................... 24 v 3.3.1 BER for M Q A M .......................................................................... 25 3.3.2 Rate and Power Adaptations ...................................................... 28 3.3.3 Numerical Results ....................................................................... 29 3.4 Discrete-Rate C a s e .................................................................................. 30 3.4.1 Problem F o rm atio n ....................................................................... 31 3.4.2 Numerical Results ....................................................................... 32 3.5 S u m m a ry .................................................................................................. 32 4 Pilot Symbol Assisted Modulation Based Channel Predictor 35 4.1 In tro d u ctio n ............................................................................................... 35 4.2 P S A M ......................................................................................................... 37 4.3 PS AM-Based Channel Prediction for an LA System ........................ 38 4.3.1 Optimal-MAP Channel Predictor ............................................ 41 4.4 Statistical Properties of the Predicted and the True Fading Am­ plitude .......................................................................................................... 44 4.4.1 The Ratio r = Q /Q ....................................................................... 45 4.4.2 Correlation Coefficient ................................................................ 46 4.4.3 Relationship between r and p .................................................. 47 4.4.4 Selection of ( L,K 0) and its impact on p .................................. 47 4.5 S u m m a ry .................................................................................................. 51 5 VRVP-MQAM System under Imperfect CSI Knowledge 52 5.1 In tro d u ctio n ............................................................................................... 52 5.2 System M o d e l ............................................................................................ 53 5.3 BER E stim ate............................................................................................ 55 5.3.1 Derivations and Results ............................................................. 56 5.4 Optimal Rate and Power Ad a p ta tio n .................................................. 60 5.5 Results and D iscussion ........................................................................... 61 vi 5.5.1 Instantaneous Rate and Power in the VRVP-MQAM-CSI S ystem ............................................................................................. 62 5.5.2 Instantaneous Rate and Power in the VRVP-MQAM System 64 5.5.3 Instantaneous Rate and Power in the CRCP-MQAM System 6 6 5.5.4 Spectral Efficiency and Average Pow er ................................
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