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Wireless Physical Layer Network Coding [Kõva köide]

(University of York),
  • Formaat: Hardback, 334 pages, kõrgus x laius x paksus: 255x180x18 mm, kaal: 810 g, Worked examples or Exercises; 5 Tables, black and white; 4 Halftones, black and white; 86 Line drawings, black and white
  • Ilmumisaeg: 15-Feb-2018
  • Kirjastus: Cambridge University Press
  • ISBN-10: 1107096111
  • ISBN-13: 9781107096110
Teised raamatud teemal:
Wireless Physical Layer Network CodingSuurem pilt
  • Formaat: Hardback, 334 pages, kõrgus x laius x paksus: 255x180x18 mm, kaal: 810 g, Worked examples or Exercises; 5 Tables, black and white; 4 Halftones, black and white; 86 Line drawings, black and white
  • Ilmumisaeg: 15-Feb-2018
  • Kirjastus: Cambridge University Press
  • ISBN-10: 1107096111
  • ISBN-13: 9781107096110
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781107096110.html
Märksõnad:
Discover a fresh approach for designing more efficient and cooperative wireless communications networks with this systematic guide. Covering everything from fundamental theory to current research topics, leading researchers describe a new, network-aware coding strategy that exploits the signal interactions that occur in dense wireless networks directly at the waveform level. Using an easy-to-follow, layered structure, this unique text begins with a gentle introduction for those new to the subject, before moving on to explain key information-theoretic principles and establish a consistent framework for wireless physical layer network coding (WPNC) strategies. It provides a detailed treatment of Network Coded Modulation, covers a range of WPNC techniques such as Noisy Network Coding, Compute and Forward, and Hierarchical Decode and Forward, and explains how WPNC can be applied to parametric fading channels, frequency selective channels, and complex stochastic networks. This is essential reading whether you are a researcher, graduate student, or professional engineer.

Leading researchers describe a new, network-aware coding strategy that exploits existing signal interactions to enhance network efficiency, capacity and security. Using a systematic, layered approach, this is an invaluable reference for researchers, graduate students and practising engineers in wireless communications and networking.

Muu info

Discover a new, network-aware coding strategy that uses existing signal interactions to enhance network efficiency, capacity and security.
Preface
xi
Mathematical Symbols xiii
Abbreviations xvi
Part I: Motivation and Gentle Introduction 1(38)
1 Introduction
3(12)
1.1 Introduction
3(1)
1.2 The "Network-Aware Physical Layer"
4(3)
1.3 Network Coding at the Network Layer
7(1)
1.4 Wireless Physical Layer Network Coding
8(3)
1.5 Historical Perspective
11(1)
1.6 Practical Usage Scenarios
12(3)
2 Wireless Physical Layer Network Coding: a Gentle Introduction
15(26)
2.1 The 2-Way Relay Channel
15(1)
2.2 Conventional, Network-Layer Network Coding, and WPNC Approaches
16(3)
2.3 WPNC Relay Strategies
19(3)
2.4 Unambiguous Decoding and Hierarchical Side-Information
22(2)
2.5 Achievable Rates of HDF and JDF
24(5)
2.5.1 Two-Source BPSK Hierarchical MAC
25(1)
2.5.2 JDF Strategy
26(1)
2.5.3 HDF Strategy
27(1)
2.5.4 Achievable Rates
28(1)
2.6 2WRC with QPSK: the Problem of Channel Parametrization
29(5)
2.7 Hierarchical Wireless Network Example
34(5)
Part II: Fundamental Principles of WPNC 39(152)
3 Fundamental Principles and System Model
41(26)
3.1 Introduction
41(1)
3.2 Scenarios and System Model
42(4)
3.2.1 Nodes
42(1)
3.2.2 Radio Resource Sharing and Network Stages
43(2)
3.2.3 Network with Cycles
45(1)
3.3 Core Principles of WPNC Network
46(10)
3.3.1 Hierarchical Principle
46(2)
3.3.2 Relay Processing Operation and Data Function
48(3)
3.3.3 Classification of Node Processing Operation Strategies
51(2)
3.3.4 Classification of Back-End Strategies
53(1)
3.3.5 Classification of Front-End Strategies
54(1)
3.3.6 Classification of Relay Node Strategy
55(1)
3.4 Global HNC Map and Generalized Exclusive Law
56(3)
3.5 Hierarchical Constellation
59(8)
3.5.1 Hierarchical Constellation and Hierarchical Codebook
59(2)
3.5.2 Common and Relative Channel Parametrization
61(3)
3.5.3 Singular Fading
64(3)
4 Components of WPNC
67(45)
4.1 Introduction
67(1)
4.2 Network Coded Modulation
67(7)
4.2.1 Multi-Source Network Structure Aware Constellation Space Codebook
67(4)
4.2.2 NCM with Hierarchical Performance Target
71(1)
4.2.3 Layered NCM
71(2)
4.2.4 Isomorphic Layered NCM
73(1)
4.3 Hierarchical Decoder
74(4)
4.3.1 Relay Operation for Decoding Hierarchical Information Measure
74(1)
4.3.2 Joint-Metric Hierarchical Decoder
75(2)
4.3.3 Layered Hierarchical Decoder
77(1)
4.4 Hierarchical Demodulator
78(13)
4.4.1 H-SODEM with Marginalization
79(3)
4.4.2 H-SODEM Providing Sufficient Statistic
82(4)
4.4.3 Soft-Aided H-SODEM
86(2)
4.4.4 H-SODEM with Nonlinear Preprocessor
88(3)
4.5 Hierarchical Error Probability Performance
91(8)
4.5.1 Hierarchical Pairwise Error Probability
91(1)
4.5.2 Hierarchical Pairwise Error Probability for Isomorphic NCM
91(2)
4.5.3 H-PEP for Gaussian Memoryless Channel
93(2)
4.5.4 Hierarchical Distance and Self-Distance Spectrum
95(1)
4.5.5 NCM Design Rules Based on H-PEP
96(3)
4.6 Hierarchical Side-Information Decoding
99(7)
4.6.1 Hierarchical Side-Information Decoding-System Model
99(5)
4.6.2 HSI-Decoding Processing Structure
104(2)
4.7 Hierarchical Network Code Map
106(6)
4.7.1 Linear HNC Map Designs
106(2)
4.7.2 HNC Maps for Linear Isomorphic Layered NCM
108(4)
5 WPNC in Cloud Communications
112(81)
5.1 Introduction
112(1)
5.2 Hierarchical Structure and Stages of Wireless Cloud
112(15)
5.2.1 Hierarchical Network Transfer Function
112(6)
5.2.2 Half-Duplex Constrained Stage Scheduling
118(9)
5.3 Information-Theoretic Limits
127(3)
5.3.1 Information-Theoretic Assessment of WPNC
127(1)
5.3.2 Information-Theoretic System Model
127(2)
5.3.3 Cut-Set Bound for Multicast Network
129(1)
5.4 Noisy Network Coding
130(9)
5.4.1 Core Principle
130(1)
5.4.2 Block Structure
131(1)
5.4.3 Transmission Step Codebooks and Encoding
132(1)
5.4.4 Compression Step Codebooks and Encoding
133(2)
5.4.5 Node Block Relay Processing
135(1)
5.4.6 Final Destination Decoding
135(1)
5.4.7 Achievable Rates
136(1)
5.4.8 Equivalent Model
136(2)
5.4.9 Noisy Network Coding in the Perspective of WPNC
138(1)
5.5 Gaussian Networks
139(5)
5.5.1 Gaussian Networks
139(1)
5.5.2 Cut-Set Bound for Multicast Gaussian Network
139(1)
5.5.3 NNC Achievable Rates for Gaussian Network
140(2)
5.5.4 Examples
142(2)
5.6 Compute and Forward
144(13)
5.6.1 Core Principle
144(1)
5.6.2 Simplified Motivation Example
145(2)
5.6.3 Nested Lattice Codebooks for H-MAC
147(1)
5.6.4 H-Codeword with Complex Integer Linear HNC Map
148(1)
5.6.5 Hierarchical Euclidean Lattice Decoding
149(1)
5.6.6 Equivalent Hierarchical Modulo Lattice Channel
149(2)
5.6.7 Optimized Single-Tap Linear MMSE Equalizer
151(1)
5.6.8 Achievable Computation Rate
152(1)
5.6.9 Special Cases
152(2)
5.6.10 Multiple Relays
154(1)
5.6.11 Compute and Forward in the Perspective of WPNC
155(1)
5.6.12 Examples
156(1)
5.7 Hierarchical Decode and Forward in Single-Stage H-MAC
157(27)
5.7.1 System Model
159(1)
5.7.2 HDF Decoding
159(1)
5.7.3 Joint-Metric Hierarchical Decoding on Product Codebook
160(5)
5.7.4 Layered Hierarchical Decoding for Isomorphic Layered NCM
165(8)
5.7.5 Properties of Hierarchical Mutual Information
173(1)
5.7.6 HDF Coding Converse Rate
174(6)
5.7.7 Hierarchical Capacity
180(2)
5.7.8 Finite Alphabet Regular Layered NCM in Linear Memoryless Gaussian Channel
182(2)
5.8 End-to-End Solvability
184(9)
5.8.1 Global Linear HNC Map
184(1)
5.8.2 Solvability of Linear HNC Map
184(1)
5.8.3 Solving Linear Ring-Based HNC Maps
185(1)
5.8.4 H-Processing Operations
186(5)
Part III: Design of Source, Relay, and Destination Strategies 191(93)
6 NCM and Hierarchical Decoding Design for H-MAC
193(14)
6.1 Introduction
193(1)
6.2 NCM with HNC Maps Adapted to Channel Parameters
193(3)
6.2.1 System Model
193(1)
6.2.2 H-Decoding
194(1)
6.2.3 Channel Optimized HNC Maps
194(2)
6.3 Layered NCM and Layered H-Decoding Design
196(11)
6.3.1 System Model
197(1)
6.3.2 Linear Isomorphic Layered NCM
198(1)
6.3.3 H-Decoding
199(1)
6.3.4 Linear HNC Maps on Extended GF
200(2)
6.3.5 H-Coding Rates
202(5)
7 NCM Design and Processing for Parametric Channels
207(19)
7.1 Introduction
207(1)
7.2 Synchronization and Pilot Design
208(7)
7.2.1 Synchronization and Channel State Estimation in WPNC Context
208(1)
7.2.2 Fundamental Limits for Phase and Magnitude Estimators in Linear AWGN H-MAC
209(5)
7.2.3 Channel State Estimators for Linear AWGN H-MAC
214(1)
7.3 NCM in Frequency Selective H-MAC Channel
215(4)
7.3.1 Block-Constant Frequency Selective H-MAC Channel
215(2)
7.3.2 NCM with OFDM Waveform
217(2)
7.4 NCM Design for Parametric Channels
219(7)
7.4.1 Parameter Invariant and Uniformly Most Powerful Design
219(1)
7.4.2 H-Distance Criterion Parametric Design
220(4)
7.4.3 Tx-Based Adaptation and Diversity-Based Solutions
224(2)
8 NCM Design for Partial HSI and Asymmetric H-MAC
226(25)
8.1 Introduction
226(1)
8.2 NCM for Multi-Map H-MAC
227(9)
8.2.1 Design Goals
227(1)
8.2.2 Structured NCM for Multi-Map H-MAC
228(1)
8.2.3 Achievable H-rate Region for Multi-Map H-MAC
229(7)
8.3 Structured NCM Design
236(15)
8.3.1 Layered Block-Structured NCM
236(1)
8.3.2 Layered Superposition-Structured NCM
237(7)
8.3.3 CF-Based Superposition-Structured NCM
244(7)
9 Joint Hierarchical Interference Processing
251(19)
9.1 Introduction
251(1)
9.2 Joint Hierarchical Interference Processing
251(1)
9.3 Joint Hierarchical Interference Processing in CF-Based NCM
252(13)
9.3.1 Integer-Constrained H-Ifc Cancellation
253(3)
9.3.2 Successive Nulling of HNC Map Coefficients
256(2)
9.3.3 Joint Hierarchical Successive CF Decoding
258(5)
9.3.4 H-SCFD with Decoupled Coefficient Optimization
263(2)
9.4 Joint Hierarchical Interference Cancellation for Isomorphic Layered NCM
265(5)
9.4.1 Equivalent Hierarchical Channel with Joint H-Ifc Cancellation
265(1)
9.4.2 Achievable H-rate with H-Ifc Cancellation
265(3)
9.4.3 Conditional Regularity for Linear GF HNC Maps
268(2)
10 WPNC in Complex Stochastic Networks
270(14)
10.1 Principles of Wireless Cloud Coding
270(1)
10.2 Wireless Cloud-Coding-Based Design of NCM
271(9)
10.2.1 Random Channel Class H-MAC and Joint HNC Map
271(3)
10.2.2 Coding Theorems for WCC NCM
274(6)
10.3 Clustered, Nested, and Modular Cloud Framework
280(4)
10.3.1 Clustered Cloud
281(1)
10.3.2 Nested Cloud
282(1)
10.3.3 Modular Cloud Framework
283(1)
Appendix A: Background Theory and Selected Fundamentals 284(29)
A.1 Basic Mathematical Definitions
284(1)
A.2 Linear Algebra
284(3)
A.2.1 Algebraic Structures
284(2)
A.2.2 Matrix Analysis
286(1)
A.2.3 Miscellaneous
287(1)
A.3 Detection, Decoding, and Estimation Theory
287(7)
A.3.1 Bayesian Estimators
287(2)
A.3.2 Maximum Likelihood Estimator
289(1)
A.3.3 MAP Sequence and Symbol Decoding
290(1)
A.3.4 Pairwise Error Union Upper Bound
290(2)
A.3.5 Complex-Valued Optimization
292(1)
A.3.6 Cramer-Rao Lower Bound
293(1)
A.3.7 Sufficient Statistic
294(1)
A.4 Information Theory
294(10)
A.4.1 Basic Concepts
294(7)
A.4.2 Capacity Region and Bounds
301(3)
A.5 Lattice Coding
304(9)
A.5.1 Lattices
304(2)
A.5.2 Lattice Coding
306(7)
References 313(3)
Index 316
Jan Sykora is a professor in the Faculty of Electrical Engineering at the Czech Technical University in Prague, and a consultant for the communications industry in the fields of advanced coding and signal processing. Alister Burr is Professor of Communications in the Department of Electronic Engineering at the University of York.