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Order Statistics in Wireless Communications: Diversity, Adaptation, and Scheduling in MIMO and OFDM Systems [Kõva köide]

(University of Victoria, Canada), (King Abdullah University of Science and Technology, Saudi Arabia)
  • Formaat: Hardback, 272 pages, kõrgus x laius x paksus: 254x180x16 mm, kaal: 680 g, Worked examples or Exercises; 8 Tables, black and white; 78 Line drawings, unspecified
  • Ilmumisaeg: 08-Sep-2011
  • Kirjastus: Cambridge University Press
  • ISBN-10: 0521199255
  • ISBN-13: 9780521199254
Teised raamatud teemal:
Order Statistics in Wireless Communications: Diversity, Adaptation, and Scheduling in MIMO and OFDM SystemsSuurem pilt
  • Formaat: Hardback, 272 pages, kõrgus x laius x paksus: 254x180x16 mm, kaal: 680 g, Worked examples or Exercises; 8 Tables, black and white; 78 Line drawings, unspecified
  • Ilmumisaeg: 08-Sep-2011
  • Kirjastus: Cambridge University Press
  • ISBN-10: 0521199255
  • ISBN-13: 9780521199254
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780521199254.html
Märksõnad:
"Covering fundamental principles through to practical applications, this self-contained guide describes indispensable mathematical tools for the analysis and design of advanced wireless transmission and reception techniques in MIMO and OFDM systems. The analysis-oriented approach develops a thorough understanding of core concepts and discussion of various example schemes shows how to apply these concepts in practice. The book focuses on techniques for advanced diversity combining, channel adaptive transmission and multiuser scheduling, the foundations of future wireless systems for the delivery of highly spectrum-efficient wireless multimedia services. Bringing together conventional and novel results from a wide variety of sources, it will teach you to accurately quantify trade-offs between performance and complexity for different design options so that you can determine the most suitable design choice based on your specific practical implementation constraints"--

"The wireless communication industry has been and is still experiencing an exciting era of rapid development. New technologies and designs emerge on a regular basis. The timely adoption of these technologies in real-world systems relies heavily on the accurate prediction of their performance over general wireless fading channels and the associated system complexity. Theoretical performance and complexity analysis become invaluable in this process, because they can help circumvent the time-consuming computer simulation and expensive field test campaigns. These analytical results, usually in the form of elegant closed-form solutions, will also bring important insight into the dependence of the performance as well as complexity measures on system design parameters and, as such, facilitate the determination of the most suitable design choice in the face of practical implementation constraints. Mathematical and statistical tools play a critical rule in the performance analysis of digital wireless communication systems over fading channels [ 1]. In fact, the proper utilization of these tools can help either simplify the existing results, which do not allow for efficient numerical evaluation, or render new analytical solutions that were previously deemed infeasible. One popular example is the application of moment generation function (MGF) in the performance analysis of digital communication system over fading channels"--

Provided by publisher.

Arvustused

' this work will be a great source of inspiration to researchers wishing to gain knowledge on the powerful statistical theory of order statistics with the applications to MIMO and OFDM systems analysis.' IEEE Communications Magazine

Muu info

A guide to indispensable mathematical tools for the analysis and design of advanced wireless transmission and reception techniques.
Preface xi
Notation xiv
1 Introduction
1(6)
1.1 Order statistics in wireless system analysis
2(1)
1.2 Diversity, adaptation, and scheduling
3(1)
1.3 Outline of the book
4(3)
2 Digital communications over fading channels
7(33)
2.1 Introduction
7(1)
2.2 Statistical fading channel models
7(9)
2.2.1 Path loss and shadowing
8(2)
2.2.2 Multipath fading
10(3)
2.2.3 Frequency-flat fading
13(2)
2.2.4 Channel correlation
15(1)
2.3 Digital wireless communications
16(10)
2.3.1 Linear bandpass modulation
16(4)
2.3.2 Performance analysis over fading channels
20(3)
2.3.3 Adaptive transmission
23(3)
2.4 Diversity combining techniques
26(11)
2.4.1 Antenna reception diversity
26(4)
2.4.2 Threshold combining and its variants
30(5)
2.4.3 Transmit diversity
35(2)
2.5 Summary
37(1)
2.6 Bibliography notes
38(2)
3 Distributions of order statistics
40(32)
3.1 Introduction
40(1)
3.2 Basic distribution functions
40(2)
3.2.1 Marginal and joint distributions
40(1)
3.2.2 Conditional distributions
41(1)
3.3 Distribution of the partial sum of largest order statistics
42(4)
3.3.1 Exponential special case
43(1)
3.3.2 General case
44(2)
3.4 Joint distributions of partial sums
46(7)
3.4.1 Cases involving all random variables
46(3)
3.4.2 Cases only involving the largest random variables
49(4)
3.5 MGF-based unified analytical framework for joint distributions
53(8)
3.5.1 General steps
54(1)
3.5.2 Illustrative examples
55(6)
3.6 Limiting distributions of extreme order statistics
61(2)
3.7 Summary
63(1)
3.8 Bibliography notes
63(9)
4 Advanced diversity techniques
72(25)
4.1 Introduction
72(1)
4.2 Generalized selection combining (GSC)
72(3)
4.2.1 Statistics of output SNR
73(2)
4.3 GSC with threshold test per branch (T-GSC)
75(3)
4.3.1 Statistics of output SNR
70(8)
4.3.2 Average number of combined paths
78(1)
4.4 Generalized switch and examine combining (GSEC)
78(6)
4.4.1 Statistics of output SNR
80(1)
4.4.2 Average number of path estimations
81(1)
4.4.3 Numerical examples
82(2)
4.5 GSEC with post-examining selection (GSECps)
84(9)
4.5.1 Statistics of output SNR
85(4)
4.5.2 Complexity analysis
89(1)
4.5.3 Numerical examples
90(3)
4.6 Summary
93(1)
4.7 Bibliography notes
93(4)
5 Adaptive transmission and reception
97(65)
5.1 Introduction
97(1)
5.2 Output-threshold MRC
98(6)
5.2.1 Statistics of output SNR
100(3)
5.2.2 Power saving analysis
103(1)
5.3 Minimum selection GSC
104(11)
5.3.1 Mode of operation
105(1)
5.3.2 Statistics of output SNR
106(7)
5.3.3 Complexity savings
113(2)
5.4 Output-threshold GSC
115(12)
5.4.1 Complexity analysis
118(4)
5.4.2 Statistics of output SNR
122(5)
5.5 Adaptive transmit diversity
127(8)
5.5.1 Mode of operation
128(2)
5.5.2 Statistics of received SNR
130(5)
5.6 RAKE finger management over the soft handoff region
135(9)
5.6.1 Finger management schemes
136(1)
5.6.2 Statistics of output SNR
137(3)
5.6.3 Complexity analysis
140(4)
5.7 Joint adaptive modulation and diversity combining
144(14)
5.7.1 Power-efficient AMDC scheme
146(2)
5.7.2 Bandwidth-efficient AMDC scheme
148(2)
5.7.3 Bandwidth-efficient and power-greedy AMDC scheme
150(4)
5.7.4 Numerical examples
154(4)
5.8 Summary
158(1)
5.9 Bibliography notes
158(4)
6 Multiuser scheduling
162(31)
6.1 Introduction
162(1)
6.2 Multiuser diversity
163(5)
6.2.1 Addressing fairness
164(2)
6.2.2 Feedback load reduction
166(2)
6.3 Performance analysis of multiuser selection diversity
168(3)
6.3.1 Absolute SNR-based scheduling
168(2)
6.3.2 Normalized SNR-based scheduling
170(1)
6.4 Multiuser parallel scheduling
171(11)
6.4.1 Generalized selection multiuser scheduling (GSMuS)
172(2)
6.4.2 On off based scheduling (OOBS)
174(2)
6.4.3 Switched-based scheduling (SBS)
176(4)
6.4.4 Numerical examples
180(2)
6.5 Power allocation for SBS
182(7)
6.5.1 Power reallocation algorithms
183(1)
6.5.2 Performance analysis
184(2)
6.5.3 Numerical examples
186(3)
6.6 Summary
189(1)
6.7 Bibliography notes
189(4)
7 Multiuser MIMO systems
193(52)
7.1 Introduction
193(1)
7.2 Basics of MIMO wireless communications
194(4)
7.2.1 MIMO channel capacity
194(2)
7.2.2 Multiuser MIMO systems
196(2)
7.3 ZFBF-based system with user selection
198(8)
7.3.1 Zeroforcing beamforming transmission
198(2)
7.3.2 User selection strategies
200(1)
7.3.3 Sum-rate analysis
201(4)
7.3.4 Numerical examples
205(1)
7.4 RUB-based system with user selection
206(16)
7.4.1 User selection strategies
208(1)
7.4.2 Asymptotic analysis for BBSI strategy
209(1)
7.4.3 Statistics of ordered-beam SINRs
210(2)
7.4.4 Sum-rate analysis
212(10)
7.5 RUB with conditional best-beam index feedback
222(7)
7.5.1 Mode of operation and feedback load analysis
223(2)
7.5.2 Sum-rate analysis
225(4)
7.6 RUB performance enhancement with linear combining
229(12)
7.6.1 System and channel model
231(1)
7.6.2 M beam feedback strategy
232(2)
7.6.3 Best-beam feedback strategy
234(7)
7.7 Summary
241(1)
7.8 Bibliography notes
241(4)
References 245(10)
Index 255
Hong-Chuan Yang is an Associate Professor in the Electrical and Computer Engineering Department at the University of Victoria, Canada. He has developed several mathematical tools for accurate performance evaluation of advanced wireless transmission technologies in fading environments and his current research focuses on channel modelling, diversity techniques, system performance evaluation, cross-layer design and energy efficient communications. Mohamed-Slim Alouini is a Professor of Electrical Engineering at KAUST, Saudi Arabia. A Fellow of the IEEE, he is a co-recipient of numerous best paper awards, including awards from ICC, Globecom, VTC and PIMRC. His research interests include design and performance analysis of diversity combining techniques, MIMO techniques, multi-hop/cooperative communications, cognitive radio, and multi-resolution, hierarchical and adaptive modulation schemes.