Wireless Communications over MIMO Channels: Applications to CDMA and Multiple Antenna Systems

380 Pages·2009·3.76 MB·English

by  Volker Kuhn(auth.)

Wireless Communications over
MIMO Channels
Wireless Communications over MIMO Channels: Applications to CDMA and Multiple Antenna Systems. Volker Kühn
 2006 John Wiley & Sons, Ltd. ISBN: 0-470-02716-9
Wireless Communications over
MIMO Channels
Applications to CDMA and Multiple Antenna Systems
Volker Ku¨hn
Universita¨t Rostock, Germany
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Contents
Preface xi
Acknowledgements xv
List of Abbreviations xvii
List of Symbols xxi
1 Introduction to Digital Communications 1
1.1 Basic System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.2 Multiple Access Techniques . . . . . . . . . . . . . . . . . . . . . . 3
1.1.3 Principle Structure of SISO Systems . . . . . . . . . . . . . . . . . 5
1.2 Characteristics of Mobile Radio Channels . . . . . . . . . . . . . . . . . . . 8
1.2.1 Equivalent Baseband Representation . . . . . . . . . . . . . . . . . 8
1.2.2 Additive White Gaussian Noise . . . . . . . . . . . . . . . . . . . . 11
1.2.3 Frequency-Selective Time-Variant Fading. . . . . . . . . . . . . . . 12
1.2.4 Systems with Multiple Inputs and Outputs . . . . . . . . . . . . . . 16
1.3 Signal Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.3.1 Optimal Decision Criteria . . . . . . . . . . . . . . . . . . . . . . . 18
1.3.2 Error Probability for AWGN Channel . . . . . . . . . . . . . . . . . 20
1.3.3 Error and Outage Probability for Flat Fading Channels . . . . . . . 22
1.3.4 Time-Discrete Matched Filter . . . . . . . . . . . . . . . . . . . . . 25
1.4 Digital Linear Modulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
1.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
1.4.2 Amplitude Shift Keying (ASK) . . . . . . . . . . . . . . . . . . . . 28
1.4.3 Quadrature Amplitude Modulation (QAM) . . . . . . . . . . . . . . 30
1.4.4 Phase Shift Keying (PSK) . . . . . . . . . . . . . . . . . . . . . . . 33
1.5 Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
1.5.1 General Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
1.5.2 MRC for Independent Diversity Branches . . . . . . . . . . . . . . 40
1.5.3 MRC for Correlated Diversity Branches . . . . . . . . . . . . . . . 47
1.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
vi CONTENTS
2 Information Theory 51
2.1 Basic Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
2.1.1 Information, Redundancy, and Entropy . . . . . . . . . . . . . . . . 51
2.1.2 Conditional, Joint and Mutual Information . . . . . . . . . . . . . . 53
2.1.3 Extension for Continuous Signals . . . . . . . . . . . . . . . . . . . 56
2.1.4 Extension for Vectors and Matrices . . . . . . . . . . . . . . . . . . 57
2.2 Channel Coding Theorem for SISO Channels . . . . . . . . . . . . . . . . . 58
2.2.1 Channel Capacity. . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
2.2.2 Cutoff Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
2.2.3 Gallager Exponent . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
2.2.4 Capacity of the AWGN Channel . . . . . . . . . . . . . . . . . . . 64
2.2.5 Capacity of Fading Channel . . . . . . . . . . . . . . . . . . . . . . 68
2.2.6 Channel Capacity and Diversity . . . . . . . . . . . . . . . . . . . . 70
2.3 Channel Capacity of MIMO Systems . . . . . . . . . . . . . . . . . . . . . 73
2.4 Channel Capacity for Multiuser Communications . . . . . . . . . . . . . . . 78
2.4.1 Single Antenna AWGN Channel . . . . . . . . . . . . . . . . . . . 78
2.4.2 Single Antenna Flat Fading Channel . . . . . . . . . . . . . . . . . 82
2.4.3 Multiple Antennas at Transmitter and Receiver. . . . . . . . . . . . 85
2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
3 Forward Error Correction Coding 91
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
3.2 Linear Block Codes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
3.2.1 Description by Matrices . . . . . . . . . . . . . . . . . . . . . . . . 94
3.2.2 Simple Parity Check and Repetition Codes . . . . . . . . . . . . . . 97
3.2.3 Hamming and Simplex Codes . . . . . . . . . . . . . . . . . . . . . 98
3.2.4 Hadamard Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
3.2.5 Trellis Representation of Linear Block Codes . . . . . . . . . . . . 99
3.3 Convolutional Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
3.3.1 Structure of Encoder . . . . . . . . . . . . . . . . . . . . . . . . . . 101
3.3.2 Graphical Description of Convolutional Codes . . . . . . . . . . . . 104
3.3.3 Puncturing Convolutional Codes . . . . . . . . . . . . . . . . . . . 105
3.3.4 ML Decoding with Viterbi Algorithm . . . . . . . . . . . . . . . . . 106
3.4 Soft-Output Decoding of Binary Codes . . . . . . . . . . . . . . . . . . . . 109
3.4.1 Log-Likelihood Ratios – A Measure of Reliability . . . . . . . . . . 109
3.4.2 General Approach for Soft-Output Decoding . . . . . . . . . . . . . 112
3.4.3 Soft-Output Decoding for Walsh Codes . . . . . . . . . . . . . . . . 114
3.4.4 BCJR Algorithm for Binary Block Codes . . . . . . . . . . . . . . 115
3.4.5 BCJR Algorithm for Binary Convolutional Codes . . . . . . . . . . 118
3.4.6 Implementation in Logarithmic Domain . . . . . . . . . . . . . . . 120
3.5 Performance Evaluation of Linear Codes . . . . . . . . . . . . . . . . . . . 121
3.5.1 Distance Properties of Codes . . . . . . . . . . . . . . . . . . . . . 121
3.5.2 Error Rate Performance of Codes . . . . . . . . . . . . . . . . . . . 125
3.5.3 Information Processing Characteristic . . . . . . . . . . . . . . . . . 131
CONTENTS vii
3.6 Concatenated Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
3.6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
3.6.2 Performance Analysis for Serial Concatenation. . . . . . . . . . . . 137
3.6.3 Performance Analysis for Parallel Concatenation . . . . . . . . . . . 141
3.6.4 Turbo Decoding of Concatenated Codes . . . . . . . . . . . . . . . 146
3.6.5 EXIT Charts Analysis of Turbo Decoding . . . . . . . . . . . . . . 153
3.7 Low-Density Parity Check (LDPC) Codes . . . . . . . . . . . . . . . . . . 160
3.7.1 Basic Definitions and Encoding . . . . . . . . . . . . . . . . . . . . 160
3.7.2 Graphical Description . . . . . . . . . . . . . . . . . . . . . . . . . 165
3.7.3 Decoding of LDPC Codes . . . . . . . . . . . . . . . . . . . . . . . 167
3.7.4 Performance of LDPC Codes . . . . . . . . . . . . . . . . . . . . . 169
3.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
4 Code Division Multiple Access 173
4.1 Fundamentals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
4.1.1 Direct-Sequence Spread Spectrum . . . . . . . . . . . . . . . . . . . 174
4.1.2 Direct-Sequence CDMA . . . . . . . . . . . . . . . . . . . . . . . . 181
4.1.3 Single-User Matched Filter (SUMF) . . . . . . . . . . . . . . . . . 185
4.1.4 Spreading Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
4.2 OFDM-CDMA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
4.2.1 Multicarrier Transmission . . . . . . . . . . . . . . . . . . . . . . . 194
4.2.2 Orthogonal Frequency Division Multiplexing . . . . . . . . . . . . . 195
4.2.3 Combining OFDM and CDMA . . . . . . . . . . . . . . . . . . . . 200
4.3 Low-Rate Channel Coding in CDMA Systems . . . . . . . . . . . . . . . . 208
4.3.1 Conventional Coding Scheme (CCS) . . . . . . . . . . . . . . . . . 209
4.3.2 Code-Spread Scheme (CSS) . . . . . . . . . . . . . . . . . . . . . . 210
4.3.3 Serially Concatenated Coding Scheme (SCCS) . . . . . . . . . . . . 211
4.3.4 Parallel Concatenated Coding Scheme (PCCS) . . . . . . . . . . . . 214
4.3.5 Influence of MUI on Coding Schemes . . . . . . . . . . . . . . . . 216
4.4 Uplink Capacity of CDMA Systems . . . . . . . . . . . . . . . . . . . . . . 219
4.4.1 Orthogonal Spreading Codes . . . . . . . . . . . . . . . . . . . . . 220
4.4.2 Random Spreading Codes and Optimum Receiver . . . . . . . . . . 220
4.4.3 Random Spreading Codes and Linear Receivers . . . . . . . . . . . 222
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
5 Multiuser Detection in CDMA Systems 227
5.1 Optimum Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
5.1.1 Optimum Joint Sequence Detection . . . . . . . . . . . . . . . . . . 228
5.1.2 Joint Preprocessing and Subsequent Separate Decoding . . . . . . . 229
5.1.3 Turbo Detection with Joint Preprocessing and Separate Decoding. . 231
5.2 Linear Multiuser Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
5.2.1 Decorrelator (Zero-Forcing, ZF) . . . . . . . . . . . . . . . . . . . . 233
5.2.2 Minimum Mean Squared Error Receiver (MMSE) . . . . . . . . . . 236
5.2.3 Linear Parallel Interference Cancellation (PIC) . . . . . . . . . . . . 240
5.2.4 Linear Successive Interference Cancellation (SIC) . . . . . . . . . . 243
viii CONTENTS
5.3 Nonlinear Iterative Multiuser Detection . . . . . . . . . . . . . . . . . . . . 245
5.3.1 Nonlinear Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
5.3.2 Uncoded Nonlinear Interference Cancellation. . . . . . . . . . . . . 247
5.3.3 Nonlinear Coded Interference Cancellation . . . . . . . . . . . . . . 253
5.4 Combining Linear MUD and Nonlinear SIC . . . . . . . . . . . . . . . . . 258
5.4.1 BLAST-like Detection . . . . . . . . . . . . . . . . . . . . . . . . . 258
5.4.2 QL Decomposition for Zero-Forcing Solution . . . . . . . . . . . . 258
5.4.3 QL Decomposition for MMSE Solution . . . . . . . . . . . . . . . 268
5.4.4 Turbo Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270
5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
6 Multiple Antenna Systems 275
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275
6.2 Spatial Diversity Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
6.2.1 Receive Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
6.2.2 Performance Analysis of Space–Time Codes . . . . . . . . . . . . . 279
6.2.3 Orthogonal Space–Time Block Codes. . . . . . . . . . . . . . . . . 282
6.2.4 Space–Time Trellis Codes . . . . . . . . . . . . . . . . . . . . . . . 293
6.3 Multilayer Transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
6.3.1 Channel Knowledge at the Transmitter and Receiver . . . . . . . . 304
6.3.2 Channel Knowledge only at the Receiver . . . . . . . . . . . . . . . 306
6.3.3 Performance of Multilayer Detection Schemes . . . . . . . . . . . . 308
6.3.4 Lattice Reduction-Aided Detection . . . . . . . . . . . . . . . . . . 312
6.4 Linear Dispersion Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
6.4.1 LD Description of Alamouti’s Scheme . . . . . . . . . . . . . . . . 320
6.4.2 LD Description of Multilayer Transmissions . . . . . . . . . . . . . 321
6.4.3 LD Description of Beamforming . . . . . . . . . . . . . . . . . . . 321
6.4.4 Optimizing Linear Dispersion Codes . . . . . . . . . . . . . . . . . 322
6.4.5 Detection of Linear Dispersion Codes. . . . . . . . . . . . . . . . . 323
6.5 Information Theoretic Analysis . . . . . . . . . . . . . . . . . . . . . . . . 323
6.5.1 Uncorrelated MIMO Channels . . . . . . . . . . . . . . . . . . . . . 323
6.5.2 Correlated MIMO Channels . . . . . . . . . . . . . . . . . . . . . . 325
6.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328
Appendix A Channel Models 329
A.1 Equivalent Baseband Representation . . . . . . . . . . . . . . . . . . . . . . 329
A.2 Typical Propagation Profiles for Outdoor Mobile Radio Channels . . . . . . 330
A.3 Moment-Generating Function for Ricean Fading . . . . . . . . . . . . . . . 331
Appendix B Derivations for Information Theory 333
B.1 Chain Rule for Entropies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
B.2 Chain Rule for Information . . . . . . . . . . . . . . . . . . . . . . . . . . 333
B.3 Data-Processing Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . 334
Appendix C Linear Algebra 335
C.1 Selected Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
CONTENTS ix
C.2 Householder Reflections and Givens Rotation. . . . . . . . . . . . . . . . . 341
C.3 LLL Lattice Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
Bibliography 347
Index 359
Preface
Motivation
Mobile radio communications are evolving from pure telephony systems to multimedia
platforms offering a variety of services ranging from simple file transfers and audio and
video streaming, to interactive applications and positioning tasks. Naturally, these services
have different constraints concerning data rate, delay, and reliability (quality-of-service
(QoS)). Hence, future mobile radio systems have to provide a large flexibility and scal-
ability to match these heterogeneous requirements. Additionally, bandwidth has become
an extremely valuable resource emphasizing the need for transmission schemes with high
spectral efficiency. To cope with these challenges, three key areas have been the focus of
research in the last decade and are addressed in this book: Code division multiple access
(CDMA), multiple antenna systems, and strong error control coding.
CDMA was chosen as a multiple access scheme in third generation mobile radio sys-
tems such as the universal mobile telecommunication system (UMTS) and CDMA 2000.
The main ingredient of CDMA systems is the inherent spectral spreading that allows a
certain coexistence with narrow band systems. Owing to the large bandwidth, it generally
provides a higher diversity degree and thus a better link reliability. Compared to second
generationmobileradiosystems,thethirdgenerationoffersincreasedflexibilitylikediffer-
ent and much higher data rates as required for the large variety of services. The frequency
reuse factor in such cellular networks allows neighboring cells to operate at the same fre-
quency, leading to a more efficient use of the resource frequency. Moreover, this allows
simpler soft handover compared to the ‘break before make’ strategy in global system for
mobile communication (GSM) when mobile subscribers change the serving cell. The main
drawback of CDMA systems is the multiuser interference requiring appropriate detection
algorithms at the receiver.
Multipleantennasystemsrepresentthesecondmajorresearcharea.Owingtotheirhigh
potentialinimproving thesystemefficiencythey havealreadyfoundtheirwayintoseveral
standards. On one hand, multiple antennas at the receiver and transmitter allow the trans-
missionofseveralspatiallyseparateddatastreams.Forpoint-to-pointcommunications,this
is termed spacedivisionmultiplexing (SDM), and in multiuser scenarios, it is called space
division multiple access (SDMA). In both the scenarios, the system’s spectral efficiency
can be remarkably increased compared to the single antenna case. On the other hand, the
link reliability can be improved by beamforming and diverse techniques.
Asathirdresearcharea,powerfulchannelcodinglikeconcatenatedcodesorlow-density
parity check codes allows efficient communications in the vicinity of Shannon’s channel
xii PREFACE
capacity.Thisleadstoapower-efficienttransmissionthatisofparticularinterestconcerning
the battery lifetime in mobile equipment and the discussion about the electromagnetic
exposition. Certainly, all mentioned areas have to be jointly considered and should be
incorporated into third generation mobile radio systems and beyond.
Owing to the influence of the mobile radio channel, a power- and bandwidth-efficient
transmission can be obtained only with appropriate signal processing either at the trans-
mitter or the receiver. Assuming channel knowledge at the transmitter, a preequalization
ofthechannel-likeTomlinson-HarashimaPrecodingallowsverysimplereceiverstructures.
Derivatives are also applicable in multiuser downlink scenarios where a common base sta-
tion can coordinate all transmissions and avoid interference prior to transmission. Even
without channel knowledge at the transmitter, space–time coding schemes allow the full
exploitation of diversity for multiple transmit antennas and flat fading channels with a
simple matched filter at the receiver. All these techniques require joint preprocessing at a
commontransmitter,thatis,acoordinatedtransmissionhastobeimplementedandprovide
the advantage of a very simple receiver structure.
On the contrary, the generally asynchronous multiuser uplink consists of spatially sep-
aratednoncooperatingtransmitters andacommon powerful basestation.Inthis scenario,a
joint preprocessing is not possible and the receiver has to take over the part of jointly pro-
cessing the signals. The same situation occurs when multiple antennas are used for spatial
multiplexing without channel knowledge at the transmitter. At first sight, such a multiple
antenna system seems to be quite different from the CDMA uplink. However, the math-
ematical description using vector notation illustrates their similarity. Hence, the common
task of receivers in both cases is to separate and recover the interfering signals so that the
same detection algorithms can be used.
Theaimofthisbookistoexplaintheprinciplesandmainadvancesofthethreeresearch
areasmentionedabove.Moreover,thesimilaritybetweentheSDMandtheCDMAuplinkis
illustrated. Therefore, a unified description using vector notations and comprising multiple
antennaaswellasCDMAsystemsispresented.This modelcanbegeneralizedtoarbitrary
vector channels, that is, channels with multiple inputs and outputs. It is used to derive
efficient detection algorithms whose error rate performances are compared.
Structure of Book
Chapter 1: Introduction to Digital Communications
The book starts with an introduction to digital communication systems. Since the mobile
radio channel dominates the design of these systems, its statistical properties are analyzed
and appropriate models for frequency selective channels with single as well as multiple
inputs and outputs are presented. Afterwards, the basic principles of signal detection and
some general expressions for the error rate performance are derived. These results are
used in the next section to determine the performance of linear modulation schemes for
different channel models. Finally, the principle of diversity is generally discussed and the
effectsareillustratedwithnumericalresults.Theyareusedinsubsequentchaptersinwhich
frequency diversity in CDMA systems and space diversity in multiple antenna systems are
explained.