272 5.6.2.4 Transmission over a Multipath Channel using Power Control and Adaptive Modulation.. 395 7.2.3.1 Network Performance using Adaptive Antenna Arrays.. 395 7.2.3.2 Network Perfor
Trang 33G, HSPA and FDD versus TDD Networking
Trang 5S Ni, Panasonic Mobile Communication, UK
IEEE Communications Society, Sponsor
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Trang 6Copyright c2008 John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester,
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Library of Congress Cataloging-in-Publication Data
1 Wireless communication systems 2 Cellular telephone systems.
I Blogh, J S (Jonathan S.) II Title.
TK5103.2.H35 2008
621.382’1–dc22
2007046621
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
ISBN 978-0-470-75420-7 (HB)
Typeset by the authors using L A TEX software.
Printed and bound in Great Britain by Antony Rowe Ltd, Chippenham, England.
This book is printed on acid-free paper responsibly manufactured from sustainable forestry in which at least two trees are planted for each one used for paper production.
Trang 71.1 Introduction 1
1.2 Basic CDMA System 2
1.2.1 Spread Spectrum Fundamentals 2
1.2.1.1 Frequency Hopping 3
1.2.1.2 Direct Sequence 3
1.2.2 The Effect of Multipath Channels 6
1.2.3 Rake Receiver 9
1.2.4 Multiple Access 13
1.2.4.1 DL Interference 14
1.2.4.2 Uplink Interference 15
1.2.4.3 Gaussian Approximation 18
1.2.5 Spreading Codes 19
1.2.5.1 m-sequences 20
1.2.5.2 Gold Sequences 21
1.2.5.3 Extended m-sequences 21
1.2.6 Channel Estimation 22
1.2.6.1 DL Pilot-assisted Channel Estimation 22
1.2.6.2 UL Pilot-symbol Assisted Channel Estimation 23
1.2.6.3 Pilot-symbol Assisted Decision-directed Channel Estimation 24
1.2.7 Summary 26
Trang 8vi CONTENTS
1.3 Third-generation Systems 26
1.3.1 Introduction 26
1.3.2 UMTS Terrestrial Radio Access (UTRA) 29
1.3.2.1 Characteristics of UTRA 29
1.3.2.2 Transport Channels 33
1.3.2.3 Physical Channels 34
1.3.2.3.1 Dedicated Physical Channels 35
1.3.2.3.2 Common Physical Channels 37
1.3.2.3.2.1 Common Physical Channels of the FDD Mode 37
1.3.2.3.2.2 Common Physical Channels of the TDD Mode 40
1.3.2.4 Service Multiplexing and Channel Coding in UTRA 43
1.3.2.4.1 CRC Attachment 43
1.3.2.4.2 Transport Block Concatenation 43
1.3.2.4.3 Channel-coding 43
1.3.2.4.4 Radio Frame Padding 46
1.3.2.4.5 First Interleaving 46
1.3.2.4.6 Radio Frame Segmentation 46
1.3.2.4.7 Rate Matching 46
1.3.2.4.8 Discontinuous Transmission Indication 47
1.3.2.4.9 Transport Channel Multiplexing 47
1.3.2.4.10 Physical Channel Segmentation 47
1.3.2.4.11 Second Interleaving 47
1.3.2.4.12 Physical Channel Mapping 47
1.3.2.4.13 Mapping Several Multirate Services to the UL Physical Channels in FDD Mode 48
1.3.2.4.14 Mapping of a 4.1 Kbps Data Service to the DL DPDCH in FDD Mode 49
1.3.2.4.15 Mapping Several Multirate Services to the UL Physical Channels in TDD Mode 50
1.3.2.5 Variable-rate and Multicode Transmission in UTRA 52
1.3.2.6 Spreading and Modulation 52
1.3.2.6.1 Orthogonal Variable Spreading Factor Codes 55
1.3.2.6.2 Uplink Scrambling Codes 57
1.3.2.6.3 Downlink Scrambling Codes 57
1.3.2.6.4 Uplink Spreading and Modulation 58
1.3.2.6.5 Downlink Spreading and Modulation 58
1.3.2.7 Random Access 60
1.3.2.7.1 Mobile-initiated Physical Random Access Procedures 60
1.3.2.7.2 Common Packet Channel Access Procedures 61
1.3.2.8 Power Control 61
1.3.2.8.1 Closed-loop Power Control in UTRA 62
1.3.2.8.2 Open-loop Power Control in TDD Mode 62
Trang 9CONTENTS vii
1.3.2.9 Cell Identification 63
1.3.2.9.1 Cell Identification in the FDD Mode 63
1.3.2.9.2 Cell Identification in the TDD Mode 65
1.3.2.10 Handover 66
1.3.2.10.1 Intra-frequency Handover or Soft Handover 66
1.3.2.10.2 Inter-frequency Handover or Hard Handover 67
1.3.2.11 Intercell Time Synchronization in the UTRA TDD Mode 68 1.3.3 The cdma2000 Terrestrial Radio Access 68
1.3.3.1 Characteristics of cdma2000 70
1.3.3.2 Physical Channels in cdma2000 71
1.3.3.3 Service Multiplexing and Channel Coding 74
1.3.3.4 Spreading and Modulation 74
1.3.3.4.1 Downlink Spreading and Modulation 75
1.3.3.4.2 Uplink Spreading and Modulation 77
1.3.3.5 Random Access 79
1.3.3.6 Handover 81
1.3.4 Performance-enhancement Features 82
1.3.4.1 Downlink Transmit Diversity Techniques 82
1.3.4.1.1 Space Time Block Coding-based Transmit Diversity 82
1.3.4.1.2 Time-switched Transmit Diversity 82
1.3.4.1.3 Closed-loop Transmit Diversity 82
1.3.4.2 Adaptive Antennas 84
1.3.4.3 Multi-user Detection/Interference Cancellation 84
1.3.5 Summary of 3G Systems 84
1.4 Summary and Conclusions 85
2 High Speed Downlink and Uplink Packet Access 87 2.1 Introduction 87
2.2 High Speed Downlink Packet Access 88
2.2.1 Physical Layer 92
2.2.1.1 High Speed Physical Downlink Shared Channel (HS-PDSCH) 94
2.2.1.2 High Speed Shared Control Channel (HS-SCCH) 96
2.2.1.3 High Speed Dedicated Physical Control Channel (HS-DPCCH) 98
2.2.2 Medium Access Control (MAC) Layer 98
2.3 High Speed Uplink Packet Access 99
2.3.1 Physical Layer 102
2.3.1.1 E-DCH Dedicated Physical Data Channel (E-DPDCH) 104
2.3.1.2 E-DCH Dedicated Physical Control Channel (E-DPCCH) 106 2.3.1.3 EDCH HARQ Indicator Channel (E-HICH) 106
2.3.1.4 E-DCH Absolute Grant Channel (E-AGCH) 107
2.3.1.5 E-DCH Relative Grant Channel (E-RGCH) 107
2.3.2 MAC Layer 108
2.4 Implementation Issues 112
Trang 10viii CONTENTS
2.4.1 HS-SCCH Detection Algorithm 112
2.4.1.1 Viterbi’s Path Metric Difference Algorithm 112
2.4.1.2 Yamamoto–Itoh Algorithm 113
2.4.1.3 Minimum Path Metric Difference Algorithm 113
2.4.1.4 Average Path Metric Difference Algorithm 114
2.4.1.5 Frequency of Path Metric Difference Algorithm 114
2.4.1.6 Last Path Metric Difference Algorithm 114
2.4.1.7 Detection Algorithm Performances 114
2.4.2 16QAM 115
2.4.2.1 Amplitude and Phase Estimation 115
2.4.2.2 Equalizer 116
2.4.3 HARQ Result Processing Time 116
2.4.4 Crest Factor 117
3 HSDPA-style Burst-by-Burst Adaptive Wireless Transceivers 119 3.1 Motivation 119
3.2 Narrowband Burst-by-Burst Adaptive Modulation 120
3.3 Wideband Burst-by-Burst Adaptive Modulation 123
3.3.1 Channel Quality Metrics 123
3.4 Wideband BbB-AQAM Video Transceivers 126
3.5 BbB-AQAM Performance 129
3.6 Wideband BbB-AQAM Video Performance 131
3.6.1 AQAM Switching Thresholds 133
3.6.2 Turbo-coded AQAM Videophone Performance 135
3.7 Burst-by-Burst Adaptive Joint-Detection CDMA Video Transceiver 136
3.7.1 Multi-user Detection for CDMA 136
3.7.2 JD-ACDMA Modem Mode Adaptation and Signalling 138
3.7.3 The JD-ACDMA Video Transceiver 139
3.7.4 JD-ACDMA Video Transceiver Performance 141
3.8 Subband-adaptive OFDM Video Transceivers 145
3.9 Summary and Conclusions 150
4 Intelligent Antenna Arrays and Beamforming 151 4.1 Introduction 151
4.2 Beamforming 152
4.2.1 Antenna Array Parameters 152
4.2.2 Potential Benefits of Antenna Arrays in Mobile Communications 153
4.2.2.1 Multiple Beams 153
4.2.2.2 Adaptive Beams 155
4.2.2.3 Null Steering 155
4.2.2.4 Diversity Schemes 155
4.2.2.5 Reduction in Delay Spread and Multipath Fading 158
4.2.2.6 Reduction in Co-channel Interference 160
4.2.2.7 Capacity Improvement and Spectral Efficiency 161
4.2.2.8 Increase in Transmission Efficiency 161
4.2.2.9 Reduction in Handovers 161
Trang 11CONTENTS ix
4.2.3 Signal Model 162
4.2.4 A Beamforming Example 165
4.2.5 Analog Beamforming 166
4.2.6 Digital Beamforming 167
4.2.7 Element-space Beamforming 167
4.2.8 Beam-space Beamforming 168
4.3 Adaptive Beamforming 169
4.3.1 Fixed Beams 170
4.3.2 Temporal Reference Techniques 171
4.3.2.1 Least Mean Squares 174
4.3.2.2 Normalized Least Mean Squares Algorithm 176
4.3.2.3 Sample Matrix Inversion 176
4.3.2.4 Recursive Least Squares 183
4.3.3 Spatial Reference Techniques 184
4.3.3.1 Antenna Calibration 185
4.3.4 Blind Adaptation 187
4.3.4.1 Constant Modulus Algorithm 188
4.3.5 Adaptive Arrays in the Downlink 189
4.3.6 Adaptive Beamforming Performance Results 191
4.3.6.1 Two Element Adaptive Antenna Using Sample Matrix Inversion 191
4.3.6.2 Two Element Adaptive Antenna Using Unconstrained Least Mean Squares 195
4.3.6.3 Two Element Adaptive Antenna Using Normalized Least Mean Squares 197
4.3.6.4 Performance of a Three Element Adaptive Antenna Array 199 4.3.6.5 Complexity Analysis 212
4.4 Summary and Conclusions 213
5 Adaptive Arrays in an FDMA/TDMA Cellular Network 215 5.1 Introduction 215
5.2 Modelling Adaptive Antenna Arrays 216
5.2.1 Algebraic Manipulation with Optimal Beamforming 216
5.2.2 Using Probability Density Functions 218
5.2.3 Sample Matrix Inversion Beamforming 219
5.3 Channel Allocation Techniques 220
5.3.1 Overview of Channel Allocation 221
5.3.1.1 Fixed Channel Allocation 222
5.3.1.1.1 Channel Borrowing 224
5.3.1.1.2 Flexible Channel Allocation 226
5.3.1.2 Dynamic Channel Allocation 226
5.3.1.2.1 Centrally Controlled DCA Algorithms 228
5.3.1.2.2 Distributed DCA Algorithms 228
5.3.1.2.3 Locally Distributed DCA Algorithms 229
5.3.1.3 Hybrid Channel Allocation 230
5.3.1.4 The Effect of Handovers 231
Trang 12x CONTENTS
5.3.1.5 The Effect of Transmission Power Control 232
5.3.2 Simulation of the Channel Allocation Algorithms 232
5.3.2.1 The Mobile Radio Network Simulator, “Netsim” 232
5.3.2.1.1 Physical Layer Model 235
5.3.2.1.2 Shadow Fading Model 235
5.3.3 Overview of Channel Allocation Algorithms 236
5.3.3.1 Fixed Channel Allocation Algorithm 237
5.3.3.2 Distributed Dynamic Channel Allocation Algorithms 237
5.3.3.3 Locally Distributed Dynamic Channel Allocation Algorithms 238
5.3.3.4 Performance Metrics 239
5.3.3.5 Nonuniform Traffic Model 240
5.3.4 DCA Performance without Adaptive Arrays 241
5.4 Employing Adaptive Antenna Arrays 242
5.5 Multipath Propagation Environments 245
5.6 Network Performance Results 251
5.6.1 System Simulation Parameters 252
5.6.2 Non-wraparound Network Performance Results 261
5.6.2.1 Performance Results over a LOS Channel 262
5.6.2.2 Performance Results over a Multipath Channel 268
5.6.2.3 Performance over a Multipath Channel using Power Control 272
5.6.2.4 Transmission over a Multipath Channel using Power Control and Adaptive Modulation 278
5.6.2.5 Power Control and Adaptive Modulation Algorithm 281
5.6.2.6 Performance of PC-assisted, AQAM-aided Dynamic Channel Allocation 284
5.6.2.7 Summary of Non-wraparound Network Performance 291
5.6.3 Wrap-around Network Performance Results 292
5.6.3.1 Performance Results over a LOS Channel 293
5.6.3.2 Performance Results over a Multipath Channel 297
5.6.3.3 Performance over a Multipath Channel using Power Control 300
5.6.3.4 Performance of an AQAM based Network using Power Control 307
5.7 Summary and Conclusions 315
6 HSDPA-style FDD Networking, Adaptive Arrays and Adaptive Modulation 317 6.1 Introduction 317
6.2 Direct Sequence Code Division Multiple Access 318
6.3 UMTS Terrestrial Radio Access 320
6.3.1 Spreading and Modulation 321
6.3.2 Common Pilot Channel 325
6.3.3 Power Control 326
6.3.3.1 Uplink Power Control 327
6.3.3.2 Downlink Power Control 328
Trang 13CONTENTS xi
6.3.4 Soft Handover 328
6.3.5 Signal-to-interference plus Noise Ratio Calculations 329
6.3.5.1 Downlink 329
6.3.5.2 Uplink 330
6.3.6 Multi-user Detection 331
6.4 Simulation Results 332
6.4.1 Simulation Parameters 332
6.4.2 The Effect of Pilot Power on Soft Handover Results 336
6.4.2.1 Fixed Received Pilot Power Thresholds without Shadowing 336 6.4.2.2 Fixed Received Pilot Power Thresholds with 0.5 Hz Shadowing 339
6.4.2.3 Fixed Received Pilot Power Thresholds with 1.0 Hz Shadowing 342
6.4.2.4 Summary 342
6.4.2.5 Relative Received Pilot Power Thresholds without Shadowing 344
6.4.2.6 Relative Received Pilot Power Thresholds with 0.5 Hz Shadowing 346
6.4.2.7 Relative Received Pilot Power Thresholds with 1.0 Hz Shadowing 348
6.4.2.8 Summary 351
6.4.3 E c /I oPower Based Soft Handover Results 351
6.4.3.1 FixedE c /I oThresholds without Shadowing 351
6.4.3.2 FixedE c /I oThresholds with 0.5 Hz Shadowing 354
6.4.3.3 FixedE c /I oThresholds with 1.0 Hz Shadowing 355
6.4.3.4 Summary 357
6.4.3.5 RelativeE c /I oThresholds without Shadowing 358
6.4.3.6 RelativeE c /I oThresholds with 0.5 Hz Shadowing 359
6.4.3.7 RelativeE c /I oThresholds with 1.0 Hz Shadowing 361
6.4.3.8 Summary 363
6.4.4 Overview of Results 363
6.4.5 Performance of Adaptive Antenna Arrays in a High Data Rate Pedestrian Environment 365
6.4.6 Performance of Adaptive Antenna Arrays and Adaptive Modulation in a High Data Rate Pedestrian Environment 373
6.5 Summary and Conclusions 380
7 HSDPA-style FDD/CDMA Performance Using Loosely Synchronized Spreading Codes 383 7.1 Effects of Loosely Synchronized Spreading Codes on the Performance of CDMA Systems 383
7.1.1 Introduction 383
7.1.2 Loosely Synchronized Codes 384
7.1.3 System Parameters 386
7.1.4 Simulation Results 388
7.1.5 Summary 391
Trang 14xii CONTENTS
7.2 Effects of Cell Size on the UTRA Performance 392
7.2.1 Introduction 392
7.2.2 System Model and System Parameters 393
7.2.3 Simulation Results and Comparisons 395
7.2.3.1 Network Performance using Adaptive Antenna Arrays 395
7.2.3.2 Network Performance using Adaptive Antenna Arrays and Adaptive Modulation 398
7.2.4 Summary and Conclusion 400
7.3 Effects of SINR Threshold on the Performance of CDMA Systems 401
7.3.1 Introduction 401
7.3.2 Simulation Results 402
7.3.3 Summary and Conclusion 406
7.4 Network-layer Performance of Multi-carrier CDMA 407
7.4.1 Introduction 407
7.4.2 Simulation Results 413
7.4.3 Summary and Conclusions 419
8 HSDPA-style TDD/CDMA Network Performance 421 8.1 Introduction 421
8.2 UMTS FDD versus TDD Terrestrial Radio Access 422
8.2.1 FDD versus TDD Spectrum Allocation of UTRA 422
8.2.2 Physical Channels 423
8.3 UTRA TDD/CDMA System 424
8.3.1 The TDD Physical Layer 425
8.3.2 Common Physical Channels of the TDD Mode 425
8.3.3 Power Control 426
8.3.4 Time Advance 428
8.4 Interference Scenario in TDD CDMA 428
8.4.1 Mobile-to-Mobile Interference 429
8.4.2 Base Station-to-Base Station Interference 429
8.5 Simulation Results 430
8.5.1 Simulation Parameters 431
8.5.2 Performance of Adaptive Antenna Array Aided TDD CDMA Systems 433
8.5.3 Performance of Adaptive Antenna Array and Adaptive Modulation Aided TDD HSDPA-style Systems 438
8.6 Loosely Synchronized Spreading Code Aided Network Performance of UTRA-like TDD/CDMA Systems 442
8.6.1 Introduction 442
8.6.2 LS Codes in UTRA TDD/CDMA 444
8.6.3 System Parameters 445
8.6.4 Simulation Results 446
8.6.5 Summary and Conclusions 449
Trang 15CONTENTS xiii
9 The Effects of Power Control and Hard Handovers on the UTRA
9.1 A Historical Perspective on Handovers 451
9.2 Hard HO in UTRA-like TDD/CDMA Systems 452
9.2.1 Relative Pilot Power-based Hard HO 453
9.2.2 Simulation Results 454
9.2.2.1 Near-symmetric UL/DL Traffic Loads 455
9.2.2.2 Asymmetric Traffic loads 458
9.3 Power Control in UTRA-like TDD/CDMA Systems 464
9.3.1 UTRA TDD Downlink Closed-loop Power Control 464
9.3.2 UTRA TDD Uplink Closed-loop Power Control 466
9.3.3 Closed-loop Power Control Simulation Results 466
9.3.3.1 UL/DL Symmetric Traffic Loads 467
9.3.3.2 UL Dominated Asymmetric Traffic Loads 470
9.3.3.3 DL Dominated Asymmetric Traffic Loads 473
9.3.4 UTRA TDD UL Open-loop Power Control 475
9.3.5 Frame-delay-based Power Adjustment Model 476
9.3.5.1 UL/DL Symmetric Traffic Loads 480
9.3.5.2 Asymmetric Traffic Loads 483
9.4 Summary and Conclusion 486
10 Genetically Enhanced UTRA/TDD Network Performance 489 10.1 Introduction 489
10.2 The Genetically Enhanced UTRA-like TDD/CDMA System 490
10.3 Simulation Results 494
10.4 Summary and Conclusion 499
11 Conclusions and Further Research 501 11.1 Summary of FDD Networking 501
11.2 Summary of FDD versus TDD Networking 506
11.3 Further Research 511
11.3.1 Advanced Objective Functions 513
11.3.2 Other Types of GAs 513
Trang 17About the Authors
Lajos Hanzo (http://www-mobile.ecs.soton.ac.uk) FREng, FIEEE,
FIET, DSc received his degree in electronics in 1976 and his doctorate
in 1983 During his 31-year career in telecommunications he has heldvarious research and academic posts in Hungary, Germany and the UK.Since 1986 he has been with the School of Electronics and ComputerScience, University of Southampton, UK, where he holds the chair
in telecommunications He has co-authored 15 books on mobile radiocommunications totalling in excess of 10 000, published in excess of
700 research papers, acted as TPC Chair of IEEE conferences, presentedkeynote lectures and been awarded a number of distinctions Currently he is directing anacademic research team, working on a range of research projects in the field of wirelessmultimedia communications sponsored by industry, the Engineering and Physical SciencesResearch Council (EPSRC) UK, the European IST Programme and the Mobile Virtual Centre
of Excellence (VCE), UK He is an enthusiastic supporter of industrial and academic liaisonand he offers a range of industrial courses He is also an IEEE Distinguished Lecturer of boththe Communications Society (ComSoc) and the Vehicular Technology Society (VTS) as well
as a Governor of both ComSoc and the VTS For further information on research in progressand associated publications please refer to http://www-mobile.ecs.soton.ac.uk
Jonathan Blogh was awarded an MEng degree with Distinction in
Information Engineering from the University of Southampton, UK in
1997 In the same year he was also awarded the IEE Lord Lloyd
of Kilgerran Memorial Prize for his interest in and commitment tomobile radio and RF engineering Between 1997 and 2000 he conductedpostgraduate research and in 2001 he earned a PhD in mobile com-munications at the University of Southampton, UK His current areas of research includethe networking aspects of FDD and TDD mode third generation mobile cellular networks.Following a spell with Radioscape, London, UK, working as a software engineer, currently
he is a senior researcher with Anritsu, UK
Trang 18xvi ABOUT THE AUTHORS
Song Ni received his BEng degree in Information detection and
instru-mentation from Shanghai Jiaotong University in 1999 Subsequently, hewas employed by Winbond Electronics (Shanghai) Ltd as a SoftwareEngineer His primary responsibility was telecom products R & D
In 2001 he started a PhD on Intelligent Wireless Networking at theUniversity of Southampton, which was sponsored by IST SCOUTproject During four years research, he developed a simulation platformfor the UTRA TDD network layer in the UMTS WCDMA system andstudied various technologies to enhance achievable performance of UTRA systems Dr Song
Ni is currently a system engineer with Panasonic Mobile Communication, UK
Trang 19Other Wiley and IEEE Press
• R Steele, L Hanzo (Ed): Mobile Radio Communications: Second and Third tion Cellular and WATM Systems, John Wiley and IEEE Press, 2nd edition, 1999, ISBN
Wiley and IEEE Press, 2002, 737 pages
• L Hanzo, L-L Yang, E-L Kuan, K Yen: Single- and Carrier CDMA: User Detection, Space-Time Spreading, Synchronization, Networking and Standards,
Multi-John Wiley and IEEE Press, June 2003, 1060 pages
• L Hanzo, M M¨unster, T Keller, B-J Choi, OFDM and MC-CDMA for Broadband Multi-User Communications, WLANs and Broadcasting, John-Wiley and IEEE Press,
2003, 978 pages
• L Hanzo, S-X Ng, T Keller and W.T Webb, Quadrature Amplitude Modulation: From Basics to Adaptive Trellis-Coded, Turbo-Equalised and Space-Time Coded OFDM, CDMA and MC-CDMA Systems, John Wiley and IEEE Press, 2004, 1105 pages.
• L Hanzo, T Keller: An OFDM and MC-CDMA Primer, John Wiley and IEEE Press,
Trang 20xviii OTHER WILEY AND IEEE PRESS BOOKS ON RELATED TOPICS
• L Hanzo, P.J Cherriman, J Streit: Video Compression and Communications:
H.261, H.263, H.264, MPEG4 and HSDPA-Style Adaptive Turbo-Transceivers John
Wiley and IEEE Press, 2nd edition, 2007, 680 pages
Trang 21Background and Overview
Wireless communications is experiencing an explosive growth rate This high demand forwireless communications services requires increased system capacities The simplest solutionwould be to allocate more bandwidth to these services, but the electromagnetic spectrum is alimited resource, which is becoming increasingly congested [1] Furthermore, the frequencybands to be used for the Third-Generation (3G) wireless services have been auctioned invarious European countries, such as Germany and the UK, at an extremely high price.Therefore, the efficient use of the available frequencies is paramount [1, 2]
The digital transmission techniques of the Second-Generation (2G) mobile radio works have already improved upon the capacity and voice quality attained by the analogmobile radio systems of the first generation However, more efficient techniques allowingmultiple users to share the available frequencies are necessary Classic techniques ofsupporting a multiplicity of users are frequency, time, polarization, code or spatial divisionmultiple access [3] In Frequency Division Multiple (FDMA) Access [4, 5] the availablefrequency spectrum is divided into frequency bands, each of which is used by a differentuser Time Division Multiple Access (TDMA) [4,5] allocates each user a given period of time,referred to as a timeslot, over which their transmission may take place The transmitter must
net-be able to store the data to net-be transmitted and then transmit it at a proportionately increasedrate during its timeslot constituting a fraction of the TDMA frame duration Alternatively,Code Division Multiple Access (CDMA) [4, 5] allocates each user a unique code This code
is then used to spread the data over a wide bandwidth shared with all users For detecting thetransmitted data the same unique code, often referred to as the user signature, must be used.The increasing demand for spectrally efficient mobile communications systems motivatesour quest for more powerful techniques With the aid of spatial processing at a cell site,optimum receive and transmit beams can be used for improving the system’s performance interms of the achievable capacity and the Quality of Service (QoS) measures This approach
is usually referred to as Spatial Division Multiple Access (SDMA) [3, 6], which enablesmultiple users in the same cell to be accommodated on the same frequency and timeslot
by exploiting the spatial selectivity properties offered by adaptive antennas [7] In contrast,
if the desired signal and interferers occupy the same frequency band and timeslot, then
Trang 22xx PREFACE
“temporal filtering” cannot be used to separate the signal from the interference However,the desired and interfering signals usually originate from different spatial locations andthis spatial separation may be exploited in order to separate the desired signal from theinterference using a “spatially selective filter” at the receiver [8–10] As a result, given asufficiently large distance between two users communicating in the same frequency band,there will be negligible interference between them The higher the number of cells in a region,owing to using small cells, the more frequently the same frequency is re-used and, hence, thehigher the teletraffic density per unit area that can be carried
However, the distance between co-channel cells must be sufficiently high so that theintra-cell interference becomes lower than its maximum acceptable limit [3] Therefore, thenumber of cells in a geographic area is limited by the base stations’ transmission power level
A method of increasing the system’s capacity is to use 120◦ sectorial beams at differentcarrier frequencies [11] Each of the sectorial beams may serve the same number of users
as supported in ordinary omni-directional cells, while the Signal-to-Interference Ratio (SIR)can be increased owing to the antenna’s directionality The ultimate solution, however, is touse independently steered high-gain beams for tracking the individual users [3] roaming inthe network
High Speed Downlink Packet Access (HSDPA)-style Adaptive Quadrature AmplitudeModulation (AQAM) [12,13] is another technique that is capable of increasing the achievablespectral efficiency The philosophy behind adaptive modulation is to select a specificmodulation mode, from a set of modes, according to the instantaneous radio channelquality [12, 13] Thus, if the channel quality exhibits a high instantaneous Signal-to-Interfaceplus Noise Ratio (SINR), then a high-order modulation mode may be employed, enabling theexploitation of the temporarily high channel capacity In contrast, if the channel has a lowinstantaneous SINR, using a high-order modulation mode would result in an unacceptablyhigh Frame Error Ratio (FER) and, hence, a more robust, but lower throughput modulationmode would be invoked Therefore, adaptive modulation not only combats the effects of apoor quality channel, but also attempts to maximize the throughput, whilst maintaining agiven target FER Thus, there is a trade-off between the mean FER and the data throughput,which is governed by the modem mode switching thresholds These switching thresholdsdefine the SINRs, at which the instantaneous channel quality requires the current modulationmode to be changed, i.e where an alternative AQAM mode must be invoked
A more explicit representation of the wideband HSDPA-style AQAM mode switchingregime is shown in Figure 1, which displays the variation of the modulation mode with respect
to the near-instantaneous SINR at average channel SNRs of 10 and 20 dB In this figure, it can
be seen explicitly that the lower-order modulation modes were chosen when the pseudo-SNRwas low In contrast, when the pseudo-SNR was high, the higher-order modulation modeswere selected in order to increase the transmission throughput This figure can also be used
to exemplify the application of wideband AQAM in an indoor and outdoor environment Inthis respect, Figure 1(a) can be used to characterize a hostile low-SINR outdoor environment,where the average channel quality was low This resulted in the utilization of predominantlymore robust modulation modes, such as Binary Phase Shift Keying (BPSK) and 4 QuadratureAmplitude Modulation (4QAM) Conversely, a less hostile high-SINR indoor environment
is exemplified by Figure 1(b), where the channel quality was consistently higher As aresult, the wideband AQAM regime can adapt by suitably invoking higher-order modula-tion modes, as evidenced by Figure 1(b) Again, this simple example demonstrated that
Trang 23BPS Pseudo SNR (dB)
(a)
Frame index
-10 -5 0 5 10 15 20 25 30
BPS Pseudo SNR (dB)
(b)
Figure 1: Modulation mode variation with respect to the pseudo-SNR evaluated at the output of the
channel equalizer of a wideband AQAM modem for transmission over the TU Rayleigh
4QAM, 16QAM and 64QAM, respectively Channel SNR of (a) 10 dB and (b) 20 dB
HSDPA-style wideband AQAM can be utilized in order to provide a seamless, instantaneous reconfiguration for example between indoor and outdoor environments Themost convincing argument in favor of HSDPA-style AQAM is that a fixed-mode systemwould increase the required uplink (UL) or downlink (DL) transmit power for the sake ofmaintaining a given user’s target Bit Error Ratio (BER), hence the system is expected toinflict a higher Multi-User Interface (MUI) upon all other system users Therefore, all of theother users would in turn also increase their power requirement, which may result in a systeminstability In contrast, an AQAM system would simply adjust the AQAM mode used, in order
near-to use the system’s resources as judiciously as possible
In this book we study the network capacity gains that may be achieved with theadvent of adaptive antenna arrays and HSDPA-style adaptive modulation techniques in bothFDMA/TDMA and CDMA-based mobile cellular networks employing Frequency DivisionDuplexing (FDD) as well as Time Division Duplexing (TDD) The advantages of employingadaptive antennas are multifold, as outlined in the following
Reduction of Co-channel Interference
Antenna arrays employed by the base station allow the implementation of spatial filtering, asshown in Figure 2, which may be exploited in both transmitting as well as receiving modes
in order to reduce co-channel interferences [1, 2, 14, 15] experienced in the UL and DL ofwireless systems When transmitting with an increased antenna gain in a certain direction
of the DL, the base station’s antenna is used to focus the radiated energy in order to form ahigh-gain directive beam in the area where the mobile receiver is likely to be This, in turn,implies that there is a reduced amount of radiated energy and, hence, reduced interferenceinflicted upon the mobile receivers roaming in other directions where the directive beamhas a lower gain The co-channel interference generated by the base station in its transmit
Trang 24xxii PREFACE
Base Station Mobile Stations
Figure 2: A cell layout showing how an antenna array can support many users on the same carrier
frequency and timeslot with the advent of spatial filtering or SDMA
mode may be further reduced by forming beams exhibiting nulls in the directions of otherreceivers [6, 16] This scheme deliberately reduces the transmitted energy in the direction ofco-channel receivers and, hence, requires prior knowledge of their positions
The employment of antenna arrays at the base station for reducing the co-channelinterference in its receive mode has been also reported widely [1, 2, 6, 16–18] This techniquedoes not require explicit knowledge of the co-channel interference signal itself, however, ithas to possess information concerning the desired signal, such as the direction of its source,
a reference signal, such as a channel sounding sequence, or a signal that is highly correlatedwith the desired signal
Capacity Improvement and Spectral Efficiency
The spectral efficiency of a wireless network refers to the amount of traffic a given systemhaving a certain spectral allocation could handle An increase in the number of users ofthe mobile communications system without a loss of performance increases the spectralefficiency Channel capacity refers to the maximum data rate a channel of a given bandwidthcan sustain An improved channel capacity leads to an ability to support more users of aspecified data rate, implying a better spectral efficiency The increased QoS that results fromthe reduced co-channel interference and reduced multipath fading [18, 19] upon using smartantennas may be exchanged for an increased number of users [2, 20]
Increase of Transmission Efficiency
An antenna array is directive in its nature, having a high gain in the direction where thebeam is pointing This property may be exploited in order to extend the range of the basestation, resulting in a larger cell size or may be used to reduce the transmitted power of themobiles The employment of a directive antenna allows the base station to receive weakersignals than an omni-directional antenna This implies that the mobile can transmit at a lowerpower and its battery recharge period becomes longer, or it would be able to use a smallerbattery, resulting in a smaller size and weight, which is important for hand-held mobiles
Trang 25PREFACE xxiii
A corresponding reduction in the power transmitted from the base station allows the use ofelectronic components having lower power ratings and, therefore, lower cost
Reduction of the Number of Handovers
When the amount of traffic in a cell exceeds the cell’s capacity, cell splitting is often used inorder to create new cells [2], each with its own base station and frequency assignment Thereduction in cell size leads to an increase in the number of handovers performed By usingantenna arrays for increasing the user capacity of a cell [1] the number of handovers requiredmay actually be reduced More explicitly, since each antenna beam tracks a mobile [2], nohandover is necessary, unless different beams using the same frequency cross each other
Avoiding Transmission Errors
When the instantaneous channel quality is low, conventional fixed-mode transceivers cally inflict a burst of transmission errors In contrast, adaptive transceivers avoid this problem
typi-by reducing the number of transmitted bits per symbol, or even typi-by disabling transmissionstemporarily The associated throughput loss can be compensated for by transmitting a highernumber of bits per symbol during the periods of relatively high channel qualities Thisadvantageous property manifests itself also in terms of an improved service quality, which
is quantified in this book in terms of the achievable video quality
However, realistic propagation scenarios are significantly more complex than thatdepicted in Figure 2 Specifically, both the desired signal and the interference sourcesexperience multipath propagation, resulting in a high number of received uplink signalsimpinging upon the base station’s receiver antenna array A result of the increased number ofreceived uplink signals is that the limited degrees of freedom of the base station’s adaptiveantenna array are exhausted, resulting in reduced nulling of the interference sources Asolution to this limitation is to increase the number of antenna elements in the base station’sadaptive array, although this has the side effect of raising the cost and complexity of the array
In a macro-cellular system it may be possible to neglect multipath rays arriving at the basestation from interfering sources, since the majority of the scatterers are located close to themobile station [21] In contrast, in a micro-cellular system the scatterers are located in boththe region of the reduced-elevation base station and that of the mobile, and hence multipathpropagation must be considered Figure 3 shows a realistic propagation environment for boththe UL and the DL, with the multipath components of the desired signal and interferencesignals clearly illustrated, where the UL and DL multipath components were assumed to
be identical for the sake of simplicity Naturally, this is not always the case and, hence, weinvestigate the potential performance gains, when the UL and DL beamforms are determinedindependently
To elaborate a little further, the design of wireless networks is based on a complexinterplay of the various performance metrics as well as on a range of other often contradictorytrade-offs, which are summarized in the stylized illustration seen in Figure 7.4 For example,Figure 7.4 suggests that it is always possible to reduce the call dropping probability byincreasing the call blocking probability, since this implies admitting less users to the system
In contrast, we may admit more users to the system for the sake of reducing the call blockingprobability, which however results in an increased call dropping probability Furthermore,
Trang 26LOS
Multipath
Basestation Beam pattern
Multipath
LOS
Multipath
Basestation Beam pattern
Interference paths
(b)
Figure 3: The multipath environments of both (a) the UL and (b) the DL, showing the multipath
components of the desired signals, the line-of-sight interference and the associated basestation antenna array beam patterns
Grade of Service Forced Termination System Complexity
Trang 27ad-we postpone the discussion of these detailed findings to our forthcoming chapters.
The various contributions on the network performance of the UMTS Terrestrial RadioAccess (UTRA) FDD and TDD modes are summarized in Table 1
The Outline of the Book
• Chapter 1 Following a brief introduction to the principles of CDMA the three
most important 3G wireless standards, namely UTRA, IMT 2000 and cdma 2000 arecharacterized The range of various transport and physical channels, the multiplexing
of various services for transmission, the aspects of channel coding are discussed Thevarious options available for supporting variable rates and a range QoS are highlighted.The UL and DL modulation and spreading schemes are described and UTRA andIMT 2000 are compared in terms of the various solutions standardized The chaptercloses with a similar portrayal of the pan-American cdma 2000 system
• Chapter 2 Since the standardization of the 3G systems substantial technological
advances have been made in adaptive modulation and coding techniques, which may
be employed to compensate for the inevitably time-variant channel quality fluctuations
of wireless channels These advances led to the definition of the HSDPA and HSUPAmodes, which are detailed in this chapter The HSDPA mode is capable of supporting
a bitrates up to about 14 MBit/s with the aid of adaptive modulation In contrast, the
UL dispenses with the employment of adaptive modulation in the interest of avoidingthe application of low-efficiency, power-hungry class-A amplification in the mobileterminal It rather employs multiple spreading sequences to increase the achievable ULbitrate, which may reach about 4 MBit/s
• Chapter 3 Following the portrayal of the HSDPA/High Speed Uplink Packet Access
(HSUPA) standards, in this chapter the HSDPA-style adaptive modulation techniquesare further detailed, which are invoked in an effort to compensate for the inevitablytime-variant channel quality fluctuations of wireless channels In this chapter wehave not restricted ourselves to standardized solutions, we have rather provided anevolutionary landscape, speculating on the types of more advanced solutions that mightfind their way into future standards, such as the extensions of the 3GPP Long-TermEvolution (LTE) project or the IEEE 802.11 Wireless Local Area Network (WLAN)standards We commence our discourse by briefly reviewing the state-of-the-art in
Trang 28xxvi PREFACE
Table 1: Contributions on the network performance of UTRA FDD and TDD cellular systems.
systems was presented
Dahlman, Gudmundson,
Nilsson and Skold [23]
Wideband Code Division Multiple Access (WCDMA)was presented as a mature technology to provide thebasis for the Universal Mobile TelecommunicationsSystem (UMTS)/IMT-2000 standards
(PRMA) was proposed as a Medium Access Control(MAC) strategy for the UL channel of the UTRATDD/CDMA mode
system was presented
Berens, Bing, Michel,Worm
and Baier [28]
The performance of low-complexity turbo-codes ployed in the UTRA TDD mode was studied
Generation Partnership Project (3GPP) was presented.Holma, Heikkinen, Lehtinen
and Toskala [30]
An interference study of the UTRA TDD system based
on simulations was provided
Aguado, O’Farrell and
UTRA-WCDMA system
Allen, Beach and Karlsson [36] The outage imposed by beamformer-based smart
antennas was studied in a UTRA FDD macro-cellenvironment
Ruiz-Garcia, Romero-Jerez
and Diaz-Estrella [37]
The effect of the MAC on QoS guarantees wasinvestigated in order to handle multimedia traffic in theUTRA system
Trang 29PREFACE xxvii
Table 1: Continued
Lott [38]
Solutions for the synchronization of ad hoc networks
based on the UTRA TDD system were proposed
and Giambene [39]
A frame-by-frame exact DL scheduling algorithmconsidering different traffic QoS levels was proposed
fuzzy-logic-control (CFLC) and designed for the UTRATDD mode was presented
modulation-aided network performance of a UTRA FDD systemwas investigated
Rummler, Chung and
Aghvami [42]
A new multicast protocol contrived for UMTS wasproposed
for multirate traffic in the UTRA system was proposed.Sivarajah and
Al-Raweshidy [44]
A comparative analysis of different Dynamic ChannelAssignment (DCA) schemes conceived for supportingongoing calls in a UTRA TDD system was presented
FDD random access channel was proposed
designed for UTRA TDD CDMA networks wasproposed
Rouse, S McLaughlin and
Band [47]
A network topology was investigated that allows bothpeer-to-peer and non-local traffic in a TDD CDMAsystem
Chinese communications TDD Special Work Groupwere disseminated
near-instantaneously adaptive modulation and introduce the associated principles Wethen apply the AQAM philosophy in the context of CDMA as well as OrthogonalFrequency Division Multiplexing (OFDM) and quantify the service-related benefits
of adaptive transceivers in terms of the achievable video quality The associatedapplication examples demonstrate the potential of the proposed adaptive techniques
in terms of tangible service quality improvements
• Chapter 4 The principles behind beamforming and the various techniques by
which it may be implemented are presented From this the concept of adaptivebeamforming is developed, and temporal as well as spatial reference techniques are ex-amined Performance results are then presented for three different temporal-reference-based adaptive beamforming algorithms, namely the Sample Matrix Inversion (SMI),
Trang 30xxviii PREFACE
Unconstrained Least Mean Squares (ULMS) and the Normalized Least Mean Squares(NLMS) algorithms
• Chapter 5 A brief summary of possible methods used for modeling the performance
of an adaptive antenna array is provided This is followed by an overview of fixedand dynamic channel allocation Multipath propagation models are then consideredfor use in our network simulations Metrics are then developed for characterizing theperformance of mobile cellular networks and our results are presented for simulationsconducted under Line-Of-Sight (LOS) propagation conditions, both with and withoutadaptive antennas Further results are then given for identical networks under multipathpropagation conditions, which are then extended to power-controlled scenarios usingboth fixed and adaptive Quadrature Amplitude Modulation (QAM) techniques Thesenetwork capacity results are obtained for both “island” type simulation areas and for
an infinite plane, using wraparound techniques
• Chapter 6 In this chapter we briefly review the 3G mobile cellular network, known
as the UTRA network, in order to enable readers to turn directly to the network-layerperformance characterization of the system, without having to consult the previouschapters This chapter then continues to present network capacity results obtainedunder various propagation conditions, in conjunction with different soft handoverthreshold metrics The performance benefits of adaptive antenna arrays are thenanalyzed, both in a non-shadowed environment and in log-normal shadow fadingconditions obeying frequencies of 0.5 and 1.0 Hz This work is then extended byinvoking HSDPA-style adaptive modulation techniques combined with beamforming,which are studied when the channel quality fluctuation is further aggravated by shadowfading
• Chapter 7 We characterize the achievable system performance of a UTRA-like
FDD CDMA system employing Loosely Synchronized (LS) spreading codes Theachievable network performance is quantified by simulation and is compared withthat of a UTRA-like FDD/CDMA system using Orthogonal Variable SpreadingFactor (OVSF) spreading codes The trade-offs between the achievable user capacityand the cell size as well as the SINR threshold are then explored We also examinethe achievable user-load and the overall performance of a Multi-Carrier Code DivisionMultiple Access (MC-CDMA)-based cellular network benefiting from both adaptiveantenna arrays and adaptive modulation techniques
• Chapter 8 In this chapter we present FDD versus TDD network capacity results
obtained under various propagation conditions The performance benefits of adaptivebeamforming and adaptive modulation techniques are analyzed These results are thencompared with those acquired when employing LS spreading codes
• Chapter 9 In this chapter, we study the effects of the hard handover margin and of
different power control schemes on the UTRA TDD/CDMA system’s performance.Both closed-loop power control as well as open-loop power control schemes aredeveloped based on the 3GPP standard A frame-delay based power adjustmentalgorithm is proposed to overcome the channel quality variations imposed by theerratically fluctuating timeslot allocations in the different interfering radio cells
Trang 31PREFACE xxix
• Chapter 10 In this chapter, we design a GA assisted UL/DL timeslot scheduling
scheme for the sake of avoiding the severe inter-cell interference caused by using theUTRA TDD/CDMA air interface
• Chapter 11 Here we give our conclusions and further work.
Contributions of the Book
• Providing an introduction to near-instantaneously adaptive modulation invoked in the
context of both single- and multi-carrier modulation or OFDM, as well as CDMA
• Quantifying the service-related benefits of HSDPA-style adaptive transceivers in the
context of wireless video telephony
• Providing an overview of the various CDMA-based 3G wireless standards.
• Study of the network performance gains using adaptive antenna arrays at the base
station in an FDMA/TDMA cellular mobile network [49, 50]
• Study of the network performance gains using adaptive antenna arrays in conjunction
with power control at the base station in an FDMA/TDMA cellular mobile network [51,52]
• Design of a combined power control and adaptive modulation assisted channel
allocation algorithm, and characterization of its performance in an FDMA/TDMAcellular mobile network [52, 53]
• Comparing the performance of various UTRA/HSDPA-style soft-handover techniques.
• Quantifying the UTRA network capacity under various channel conditions.
• Evaluating the network performance of UTRA with the aid of adaptive antenna arrays.
• Demonstrating the benefits of adaptive modulation in the context of both FDMA/
TDMA and CDMA cellular mobile networks
Our hope is that the book offers you a range of interesting topics in the era of theimminent introduction of 3G wireless networks We have attempted to provide an informativetechnological roadmap, allowing the reader to quantify the achievable network capacitygains with the advent of introducing more powerful enabling technologies in the physicallayer Analyzing the associated system design trade-offs in terms of network complexityand network capacity is the basic aim of this book We aimed for underlining the range
of contradictory system design trade-offs in an unbiased fashion, with the motivation ofproviding you with sufficient information for solving your own particular wireless networkingproblems Most of all, however, we hope that you will find this book an enjoyable andrelatively effortless reading, providing you with intellectual stimulation
Lajos Hanzo, Jonathan Blogh and Song Ni
Trang 33We are indebted to our many colleagues who have enhanced our understanding of thesubject, in particular to Prof Emeritus Raymond Steele These colleagues and valuedfriends, too numerous to be mentioned, have influenced our views concerning variousaspects of wireless multimedia communications We thank them for the enlightenment gainedfrom our collaborations on various projects, papers, and books We are grateful to JanBrecht, Marco Breiling, Marco del Buono, Sheng Chen, Peter Cherriman, Stanley Chia,Byoung Jo Choi, Joseph Cheung, Peter Fortune, Sheyam Lal Dhomeja, Lim Dongmin,Dirk Didascalou, Stephan Ernst, Eddie Green, David Greenwood, Hee Thong How, ThomasKeller, Ee Lin Kuan, W H Lam, Matthias M¨unster, C C Lee, M A Nofal, Xiao Lin,Chee Siong Lee, Tong-Hooi Liew, Jeff Reeve, Vincent Roger-Marchart, Redwan Salami,David Stewart, Clare Sommerville, Jeff Torrance, Spyros Vlahoyiannatos, William Webb,Stefan Weiss, John Williams, Jason Woodard, Choong Hin Wong, Henry Wong, James Wong,Lie-Liang Yang, Bee-Leong Yeap, Mong-Suan Yee, Kai Yen, Andy Yuen, and many otherswith whom we enjoyed an association
We also acknowledge our valuable associations with the Virtual Centre of Excellence
in Mobile Communications, in particular with its chief executive, Dr Walter Tuttlebee,and other members of its Executive Committee, namely Dr Keith Baughan, Prof HamidAghvami, Prof Mark Beach, Prof John Dunlop, Prof Barry Evans, Prof Steve MacLaughlin,Prof Joseph McGeehan and many other valued colleagues Our sincere thanks are also due
to John Hand and Nafeesa Simjee EPSRC, UK for supporting our research We would alsolike to thank Dr Joao Da Silva, Dr Jorge Pereira, Bartholome Arroyo, Bernard Barani,Demosthenes Ikonomou, and other valued colleagues from the Commission of the EuropeanCommunities, Brussels, Belgium, as well as Andy Aftelak, Mike Philips, Andy Wilton, LuisLopes, and Paul Crichton from Motorola ECID, Swindon, UK, for sponsoring some of ourrecent research Further thanks are due to Tim Wilkinson at HP in Bristol for funding some
of our research efforts
Similarly, our sincere thanks are due to Katharine Unwin, Mark Hammond, Sarah Hintonand their colleagues at Wiley in Chichester, UK, as well as Denise Harvey, who assisted
us during the production of the book Finally, our sincere gratitude is due to the numerousauthors listed in the Author Index—as well as to those, whose work was not cited due to spacelimitations—for their contributions to the state of the art, without whom this book would nothave materialized
Lajos Hanzo, Jonathan Blogh and Song Ni
Trang 35Chapter 1
Third-generation CDMA Systems
K Yen and L Hanzo
Although the number of cellular subscribers continues to grow worldwide [54], the inantly speech-, data- and e-mail-oriented services are expected to be enriched by a wholehost of new services in the near future Thus the performance of the recently standardizedCode Division Multiple Access (CDMA) third-generation (3G) mobile systems is expected
predom-to become comparable predom-to, if not better than, that of their wired counterparts
These ambitious objectives are beyond the capabilities of the present second-generation(2G) mobile systems such as the Global System for Mobile Communications known
as GSM [55], the Interim Standard-95 (IS-95) Pan-American system, or the PersonalDigital Cellular (PDC) system [56] in Japan Thus, in recent years, a range of newsystem concepts and objectives were defined, and these will be incorporated in the 3Gmobile systems Both the European Telecommunications Standards Institute (ETSI) and theInternational Telecommunication Union (ITU) are defining a framework for these systemsunder the auspices of the Universal Mobile Telecommunications System (UMTS) [54,56–60]and the International Mobile Telecommunications scheme in the year 2000 (IMT-2000)1
[57, 58, 61]
Their objectives and the system concepts will be discussed in more detail in latersections CDMA is the predominant multiple access technique proposed for the 3G wirelesscommunications systems worldwide CDMA was already employed in some 2G systems,such as the IS-95 system and it has proved to be a success Partly motivated by this success,both the Pan-European UMTS and the IMT-2000 initiatives have opted for a CDMA-basedsystem, although the European system also incorporates an element of TDMA In this chapter,
we provide a rudimentary introduction to a range of CDMA concepts Then the European,
1 Formerly known as Future Public Land Mobile Telecommunication Systems.
L Hanzo, J S Blogh and S Ni 2008 John Wiley & Sons, Ltdc
Trang 362 CHAPTER 1 THIRD-GENERATION CDMA SYSTEMS
American and Japanese CDMA-based 3G mobile system concepts are considered, followed
by a research-oriented outlook on potential future systems
The chapter is organized as follows Section 1.2 offers a rudimentary introduction
to CDMA in order to make this chapter self-contained, whereas Section 1.3 focuses onthe basic objectives and system concepts of the 3G mobile systems, highlighting theEuropean, American and Japanese CDMA-based third-generation system concepts Finally,our conclusions are presented in Section 1.4
CDMA is a spread spectrum communications technique that supports simultaneous digitaltransmission of several users’ signals in a multiple access environment Although thedevelopment of CDMA was motivated by user capacity considerations, the system capacityprovided by CDMA is similar to that of its more traditional counterparts, frequency divisionmultiple access (FDMA), and time division multiple access (TDMA) [62] However, CDMAhas the unique property of supporting a multiplicity of users in the same radio channel with
a graceful degradation in performance due to multi-user interference Hence, any reduction
in interference can lead to an increase in capacity [63] Furthermore, the frequency reusefactor in a CDMA cellular environment can be as high as unity, and being a so-calledwideband system, it can coexist with other narrowband microwave systems, which maycorrupt the CDMA signal’s spectrum in a narrow frequency band without inflicting significantinterference [64] This eases the problem of frequency management as well as allowing
a smooth evolution from narrowband systems to wideband systems But perhaps the mostglaring advantage of CDMA is its ability to combat or in fact to benefit from multipath fading,
as it will become explicit during our further discourse
In the forthcoming sections, we introduce our nomenclature, which will be usedthroughout the subsequent sections Further in-depth information on CDMA can be found
in a range of excellent research papers [62, 64, 65] and textbooks [66–69]
In spread spectrum transmission, the original information signal, which occupies a bandwidth
ofB Hz, is transmitted after spectral spreading to a bandwidth N times higher, where N is
known as the processing gain In practical terms the processing gain is typically in the range
of10− 30 dB [64] This frequency-domain spreading concept is illustrated in Figure 1.1.
The power of the transmitted spread spectrum signal is spread overN times the original
bandwidth, while its spectral density is correspondingly reduced by the same amount Hence,the processing gain is given by:
where B s is the bandwidth of the spread spectrum signal while B is the bandwidth of
the original information signal As we shall see during our further discourse, this uniquetechnique of spreading the information spectrum is the key to improving its detection in amobile radio environment, and it also allows narrowband signals exhibiting a significantlyhigher spectral density to share the same frequency band [64]
Trang 371.2 BASIC CDMA SYSTEM 3
Figure 1.1: Power spectral density of signal before and after spreading.
There are basically two main types of spread spectrum (SS) systems [62]:
• Direct Sequence (DS) SS systems and
• Frequency Hopping (FH) SS systems.
1.2.1.1 Frequency Hopping
In FH spreading, which was invoked in the 2G GSM system the narrowband signal is mitted using different carrier frequencies at different times Thus, the data signal is effectivelytransmitted over a wide spectrum There are two classes of frequency hopping patterns In fastfrequency hopping, the carrier frequency changes several times per transmitted symbol, while
trans-in slow frequency hopptrans-ing, the carrier frequency changes typically after a number of symbols
or a transmission burst In the GSM system each transmission burst of 114 channel-codedspeech bits was transmitted on a different frequency and since the TDMA frame durationwas 4.615 ms, the associated hopping frequency was its reciprocal, that is, 217 hops/s Theexact sequence of frequency hopping will be made known only to the intended receiver sothat the frequency hopped pattern may be dehopped in order to demodulate the signal [64].Direct sequence (DS) spreading is more commonly used in CDMA Hence, our forthcomingdiscussions will be in the context of direct sequence spreading
1.2.1.2 Direct Sequence
In DS spreading, the information signal is multiplied by a high-frequency signature sequence,also known as a spreading code or spreading sequence This user signature sequencefacilitates the detection of different users’ signals in order to achieve a multiple accesscapability in CDMA Although in CDMA this user “separation” is achieved using orthogonalspreading codes, in FDMA and TDMA orthogonal frequency slots or timeslots are provided,respectively
Trang 384 CHAPTER 1 THIRD-GENERATION CDMA SYSTEMS
1 -1
1 -1
1 -1
Figure 1.2: Time-domain waveforms involved in generating a direct sequence spread signal.
a(t)
√
2P b cos w c t
u(t) b(t)
s(t)
Figure 1.3: BPSK modulated DS-SS transmitter.
We can see from Figure 1.2 that each information symbol of durationT sis broken intoN c
equi-spaced subintervals of durationT c, each of which is multiplied with a different chip ofthe spreading sequence Hence,N c= T s
T c The resulting output is a high-frequency sequence.For binary signalingT s = T b, whereT b is the data bit duration Hence,N c is equal tothe processing gainN However, for M -ary signaling, where M > 2, T s = T b and hence
N c = N An understanding of the distinction between N c andN is important, since the
values ofN candN have a direct effect on the bandwidth efficiency and performance of the
CDMA system
The block diagram of a typical binary phase shift keying (BPSK) modulated DS-SStransmitter is shown in Figure 1.3 We will now express the associated signals mathematically.The binary data signal may be written as:
Trang 391.2 BASIC CDMA SYSTEM 5
1 -1
1 -1
1 -1
Figure 1.4: Time-domain waveforms involved in decoding a direct sequence signal.
whereT bis the bit duration,b j ∈ {+1, −1} denotes the jth data bit, and Γ T b (t) is the pulse
shape of the data bit In practical applications,Γτ (t) has a bandlimited waveform, such as a
raised cosine Nyquist pulse However, for analysis and simulation simplicity, we will assumethatΓτ (t) is a rectangular pulse throughout this chapter, which is defined as:
wherea h ∈ {+1, −1} denotes the hth chip and Γ T c (t) is the chip-pulse with a chip duration
ofT c The energy of the spreading sequence over a bit duration ofT bis normalized according
whereP bis the average transmitted power At the intended receiver, the signal is multiplied
by the conjugate of the transmitter’s spreading sequence, which is known as the despreadingsequence, in order to retrieve the information Ideally, in a single-user, nonfading, noiselessenvironment, the original information can be decoded without errors This is seen inFigure 1.4
In reality, however, the conditions are never so perfect The received signal will becorrupted by noise, interfered by both multipath fading—resulting in intersymbol interference
Trang 406 CHAPTER 1 THIRD-GENERATION CDMA SYSTEMS
LPF
signal Recovered
Signature sequence
Figure 1.5: BPSK DS-SS receiver for AWGN channel.
(ISI)—and by other users, generating multi-user interference Furthermore, this signal isdelayed by the time-dispersive medium It is possible to reduce the interference due tomultipath fading and other users by innovative signal processing methods, which will bediscussed in more detail in later sections
Figure 1.5 shows the block diagram of the receiver for a noise-corrupted channel using acorrelator for detecting the transmitted signal, yielding:
ˆb i= sgn
1
whereξ b = T b × P bis the bit energy and sgn(x) is the signum function of x, which returns
a value of 1, ifx > 0 and returns a value of −1, if x < 0 In a single-user Additive White
Gaussian Noise (AWGN) channel, the receiver shown in Figure 1.5 is optimum In fact, theperformance of the DS-SS system discussed so far is the same as that of a conventional BPSKmodem in an AWGN channel, whereby the probability of bit errorP r b () is given by:
In this section, we present an overview of the effects of the multipath wireless channelsencountered in a digital mobile communication system, which was treated in depth forexample in [11] Interested readers may also refer to the recent articles written by Sklar
in [71, 72] for a brief overview on this subject