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Introduction to MIMO Communications.pdf
Cover
Contents
Preface
1 Overview of MIMO communications
1.1 What is MIMO?
1.2 History of MIMO
1.3 Smart antennas vs MIMO
1.4 Single-user and multi-user MIMO
1.5 Introduction to spatial diversity
1.5.1 The concept of diversity
1.5.2 Receive and transmit diversity
1.5.3 Common diversity performance metrics
1.5.4 Relationship between diversity order and diversity gain
1.6 Introduction to spatial multiplexing
1.6.1 The concept of spatial multiplexing
1.7 Open- and closed-loop MIMO
1.8 The practical use of MIMO
1.8.1 Commercial MIMO implementations
1.8.2 Measured MIMO performance
1.9 Review of matrices
1.9.1 Basic definitions
1.9.2 Theorems and properties
Problems
2 The MIMO capacity formula
2.1 What is information?
2.2 Entropy
2.3 Mutual information
2.4 Definition of SISO capacity
2.5 Definition of MIMO capacity
2.5.1 MIMO system model
2.5.2 Capacity
2.6 Evaluating H(z)
2.7 Evaluating H(r)
2.8 Final result
2.8.1 Real signals
2.8.2 Complex signals
Problems
3 Applications of the MIMO capacity formula
3.1 MIMO capacity under the CSIR assumption
3.2 Eigen-channels and channel rank
3.3 Optimum distribution of channel eigenvalues
3.4 Eigenbeamforming
3.5 Optimal allocation of power in eigenbeamforming
3.5.1 The waterfilling algorithm
3.5.2 Discussion of the waterfilling algorithm
3.6 Single-mode eigenbeamforming
3.7 Performance comparison
3.7.1 Results for Nr ≥ Nt
3.7.2 Results for Nt > Nr
3.8 Capacities of SIMO and MISO channels
3.8.1 SIMO capacity
3.8.2 MISO capacity
3.9 Capacity of random channels
3.9.1 Definition of Hw
3.9.2 Capacity of an Hw channel for large N
3.9.3 Ergodic capacity
3.9.4 Outage capacity
Problems
4 RF propagation
4.1 Phenomenology of multipath channels
4.2 Power law propagation
4.3 Impulse response of a multipath channel
4.4 Intrinsic multipath channel parameters
4.4.1 Parameters related to τ
4.4.2 Parameters related to t
4.5 Classes of multipath channels
4.5.1 Flat fading
4.5.2 Frequency-selective fading
4.5.3 Slow and fast fading
4.6 Statistics of small-scale fading
4.6.1 Rayleigh fading
4.6.2 Rician fading
Problems
5 MIMO channel models
5.1 MIMO channels in LOS geometry
5.2 General channel model with correlation
5.3 Kronecker channel model
5.4 Impact of antenna correlation on MIMO capacity
5.5 Dependence of Rt and Rr on antenna spacing and scattering angle
5.6 Pinhole scattering
5.7 Line-of-sight channel model
Problems
6 Alamouti coding
6.1 Maximal ratio receive combining (MRRC)
6.2 Challenges with achieving transmit diversity
6.3 2 x 1 Alamouti coding
6.4 2 x Nr Alamouti coding
6.4.1 The 2 x 2 case
6.4.2 The 2 x Nr case
6.5 Maximum likelihood demodulation in MRRC and Alamouti receivers
6.6 Performance results
6.6.1 Theoretical performance analysis
6.6.2 Simulating Alamouti and MRRC systems
6.6.3 Results
Problems
7 Space-time coding
7.1 Space-time coding introduction
7.1.1 Definition of STBC code rate
7.1.2 Spectral efficiency of a STBC
7.1.3 A taxonomy of space-time codes
7.2 Space-time code design criteria
7.2.1 General pairwise error probability expression
7.2.2 Pairwise error probability in Rayleigh fading
7.2.3 Pairwise error probability in Rician fading
7.2.4 Summary of design criteria
7.3 Orthogonal space-time block codes
7.3.1 Real, square OSTBCs
7.3.2 Real, non-square OSTBCs
7.3.3 Complex OSTBCs
7.3.4 Decoding OSTBCs
7.3.5 Simulating OSTBC performance
7.3.6 OSTBC performance results
7.4 Space-time trellis codes
7.4.1 STTC encoding
7.4.2 STTC performance results
Problems
8 Spatial multiplexing
8.1 Overview of spatial multiplexing
8.2 BLAST encoding architectures
8.2.1 Vertical-BLAST (V-BLAST)
8.2.2 Horizontal-BLAST (H-BLAST)
8.2.3 Diagonal-BLAST (D-BLAST)
8.3 Demultiplexing methods for H-BLAST and V-BLAST
8.3.1 Zero-forcing (ZF)
8.3.2 Zero-forcing with interference cancellation (ZF-IC)
8.3.3 Linear minimum mean square detection (LMMSE)
8.3.4 LMMSE with interference cancellation (LMMSE-IC)
8.3.5 BLAST performance results
8.3.6 Comparison of ZF and LMMSE at large SNR
8.4 Multi-group space-time coded modulation (MGSTC)
8.4.1 The MGSTC encoder structure
8.4.2 Nomenclature
8.4.3 MGSTC decoding
8.4.4 Group-dependent diversity
8.4.5 MGSTC performance results
Problems
9 Broadband MIMO
9.1 Flat and frequency-selective fading
9.2 Strategies for coping with frequency-selective fading
9.2.1 Exploiting frequency-selective fading
9.2.2 Combating frequency-selective fading
9.3 Conventional OFDM
9.4 MIMO OFDM
9.5 OFDMA
9.6 Space-frequency block coding (SFBC)
Problems
10 Channel estimation
10.1 Introduction
10.2 Pilot allocation strategies
10.2.1 Narrowband MIMO channels
10.2.2 Broadband MIMO channels
10.2.3 Designing pilot spacing
10.2.4 Spatial pilot allocation strategies
10.3 Narrowband MIMO channel estimation
10.3.1 Maximum likelihood channel estimation
10.3.2 Least squares channel estimation
10.3.3 Linear minimum mean square channel estimation
10.3.4 Choosing pilot signals
10.3.5 Narrowband CE performance
10.4 Broadband MIMO channel estimation
10.4.1 Frequency-domain channel estimation
10.4.2 Time-frequency interpolation
Problems
11 Practical MIMO examples
11.1 WiFi
11.1.1 Overview of IEEE 802.11n
11.1.2 802.11n packet structure
11.1.3 802.11n HT transmitter architecture
11.1.4 Space-time block coding in 802.11n
11.1.5 OFDM in 802.11n
11.1.6 Channel estimation
11.1.7 Modulation and coding schemes in 802.11n
11.2 LTE
11.2.1 Overview and history
11.2.2 LTE waveform structure
11.2.3 LTE transmitter block diagrams
11.2.4 DL transmit diversity
11.2.5 Spatial multiplexing
11.2.6 LTE data rates
Problems
Appendices
A MIMO system equation normalization
B Proof of theorem 5.2
C Derivation of Eq. 7.9
D Maximum likelihood decoding rules for selected OSTBCs
E Derivation of Eq. 8.68
F Parameters for the non-unequal HT modulation and coding schemes in IEEE 802.11n
References
Index
Introduction to MIMO Communications
This accessible, self-contained guide contains everything you need to get up to speed on
the theory and implementation of MIMO techniques.
In-depth coverage of topics such as RF propagation, space-time coding, spatial mul-
tiplexing, OFDM in MIMO for broadband applications, the theoretical MIMO capacity
formula, and channel estimation, will give you a deep understanding of how the results
are obtained, while detailed descriptions of how MIMO is implemented in commercial
WiFi and LTE networks will help you apply the theory to practical wireless systems.
Key concepts in matrix mathematics and information theory are introduced and devel-
oped as you need them, and key results are derived step by step, with no details omitted.
Including numerous worked examples, and end-of-chapter exercises to reinforce and
solidify your understanding, this is the perfect introduction to MIMO for anyone new to
the field.
Jerry R. Hampton is a research engineer with over 30 years’ experience in communi-
cations systems engineering. He is a member of the principal professional staff in the
Applied Physics Laboratory, and an Adjunct Professor in the Whiting School of Engi-
neering, at The Johns Hopkins University, where he teaches a graduate course in MIMO
wireless communications.
“This is a well-organized comprehensive treatise on MIMO principles, methods, and
applications. While many concepts are introduced in intuitively pleasing ways; the
integration of detailed step-by-step mathematical developments of MIMO principles,
propagation models, channel characterizations, and applications of MIMO in commer-
cial systems adds tremendous depth and understanding to the concepts. After studying
this text, if readers have interests in topics not covered, they will very likely be able to
understand or author for themselves advanced MIMO literature on such topics.”
David Nicholson, Communications consultant
Introduction to
MIMO Communications
JERRY R. HAMPTON
The Johns Hopkins University
University Printing House, Cambridge CB2 8BS, United Kingdom
Published in the United States of America by Cambridge University Press, New York
Cambridge University Press is part of the University of Cambridge.
It furthers the University’s mission by disseminating knowledge in the pursuit of
education, learning, and research at the highest international levels of excellence.
www.cambridge.org
Information on this title: www.cambridge.org/9781107042834
c Cambridge University Press 2014
This publication is in copyright. Subject to statutory exception
and to the provisions of relevant collective licensing agreements,
no reproduction of any part may take place without the written
permission of Cambridge University Press.
First published 2014
Printed in the United Kingdom by TJ International Ltd. Padstow Cornwall
A catalog record for this publication is available from the British Library
ISBN 978-1-107-04283-4 Hardback
Additional resources for this publication at www.cambridge.org/hampton
Cambridge University Press has no responsibility for the persistence or accuracy of
URLs for external or third-party internet websites referred to in this publication,
and does not guarantee that any content on such websites is, or will remain,
accurate or appropriate.
Contents
Preface
page xi
1
2
Overview of MIMO communications
1.1 What is MIMO?
History of MIMO
1.2
Smart antennas vs MIMO
1.3
Single-user and multi-user MIMO
1.4
1.5
Introduction to spatial diversity
1.5.1
1.5.2
1.5.3
1.5.4
Introduction to spatial multiplexing
1.6.1
Open- and closed-loop MIMO
The practical use of MIMO
1.8.1
1.8.2 Measured MIMO performance
Review of matrices
1.9.1
1.9.2
Basic definitions
Theorems and properties
1.7
1.8
1.6
1.9
Commercial MIMO implementations
The concept of diversity
Receive and transmit diversity
Common diversity performance metrics
Relationship between diversity order and diversity gain
The concept of spatial multiplexing
Entropy
The MIMO capacity formula
2.1 What is information?
2.2
2.3 Mutual information
2.4
2.5
Definition of SISO capacity
Definition of MIMO capacity
2.5.1 MIMO system model
2.5.2
Capacity
Evaluating H(z)
Evaluating H(r)
Final result
2.8.1
2.8.2
Real signals
Complex signals
2.6
2.7
2.8
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vi
3
4
5
3.6
3.7
3.8
3.9
4.5
4.6
Contents
Applications of the MIMO capacity formula
3.1 MIMO capacity under the CSIR assumption
3.2
3.3
3.4
3.5
The waterfilling algorithm
Discussion of the waterfilling algorithm
Eigen-channels and channel rank
Optimum distribution of channel eigenvalues
Eigenbeamforming
Optimal allocation of power in eigenbeamforming
3.5.1
3.5.2
Single-mode eigenbeamforming
Performance comparison
3.7.1
3.7.2
Capacities of SIMO and MISO channels
3.8.1
SIMO capacity
3.8.2 MISO capacity
Capacity of random channels
3.9.1
3.9.2
3.9.3
3.9.4
Definition of Hw
Capacity of an Hw channel for large N
Ergodic capacity
Outage capacity
Results for Nr ≥ Nt
Results for Nt > Nr
RF propagation
4.1
4.2
4.3
4.4
Phenomenology of multipath channels
Power law propagation
Impulse response of a multipath channel
Intrinsic multipath channel parameters
Parameters related to τ
4.4.1
Parameters related to t
4.4.2
Classes of multipath channels
4.5.1
4.5.2
4.5.3
Statistics of small-scale fading
4.6.1
4.6.2
Flat fading
Frequency-selective fading
Slow and fast fading
Rayleigh fading
Rician fading
MIMO channel models
5.1 MIMO channels in LOS geometry
5.2
5.3
5.4
5.5
5.6
5.7
General channel model with correlation
Kronecker channel model
Impact of antenna correlation on MIMO capacity
Dependence of Rt and Rr on antenna spacing and scattering angle
Pinhole scattering
Line-of-sight channel model
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