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Wireless Physical Layer Network Coding

✍ Scribed by Jan Sýkora


Publisher
Cambridge University Press
Year
2018
Tongue
English
Leaves
338
Category
Library

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✦ Synopsis


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.

✦ Table of Contents


Contents
Preface
Mathematical Symbols
Abbreviations
Part I Motivation and Gentle Introduction
1 Introduction
1.1 Introduction
1.2 The β€œNetwork-Aware Physical Layer”
1.3 Network Coding at the Network Layer
1.4 Wireless Physical Layer Network Coding
1.5 Historical Perspective
1.6 Practical Usage Scenarios
2 Wireless Physical Layer Network Coding: a Gentle Introduction
2.1 The 2-Way Relay Channel
2.2 Conventional, Network-Layer Network Coding, and WPNC Approaches
2.3 WPNC Relay Strategies
2.4 Unambiguous Decoding and Hierarchical Side-Information
2.5 Achievable Rates of HDF and JDF
2.5.1 Two-Source BPSK Hierarchical MAC
2.5.2 JDF Strategy
2.5.3 HDF Strategy
2.5.4 Achievable Rates
2.6 2WRC with QPSK: the Problem of Channel Parametrization
2.7 Hierarchical Wireless Network Example
Part II Fundamental Principles of WPNC
3 Fundamental Principles and System Model
3.1 Introduction
3.2 Scenarios and System Model
3.2.1 Nodes
3.2.2 Radio Resource Sharing and Network Stages
3.2.3 Network with Cycles
3.3 Core Principles of WPNC Network
3.3.1 Hierarchical Principle
3.3.2 Relay Processing Operation and Data Function
3.3.3 Classification of Node Processing Operation Strategies
3.3.4 Classification of Back-End Strategies
3.3.5 Classification of Front-End Strategies
3.3.6 Classification of Relay Node Strategy
3.4 Global HNC Map and Generalized Exclusive Law
3.5 Hierarchical Constellation
3.5.1 Hierarchical Constellation and Hierarchical Codebook
3.5.2 Common and Relative Channel Parametrization
3.5.3 Singular Fading
4 Components of WPNC
4.1 Introduction
4.2 Network Coded Modulation
4.2.1 Multi-Source Network Structure Aware Constellation Space Codebook
4.2.2 NCM with Hierarchical Performance Target
4.2.3 Layered NCM
4.2.4 Isomorphic Layered NCM
4.3 Hierarchical Decoder
4.3.1 Relay Operation for Decoding Hierarchical Information Measure
4.3.2 Joint-Metric Hierarchical Decoder
4.3.3 Layered Hierarchical Decoder
4.4 Hierarchical Demodulator
4.4.1 H-SODEM with Marginalization
4.4.2 H-SODEM Providing Sufficient Statistic
4.4.3 Soft-Aided H-SODEM
4.4.4 H-SODEM with Nonlinear Preprocessor
4.5 Hierarchical Error Probability Performance
4.5.1 Hierarchical Pairwise Error Probability
4.5.2 Hierarchical Pairwise Error Probability for Isomorphic NCM
4.5.3 H-PEP for Gaussian Memoryless Channel
4.5.4 Hierarchical Distance and Self-Distance Spectrum
4.5.5 NCM Design Rules Based on H-PEP
4.6 Hierarchical Side-Information Decoding
4.6.1 Hierarchical Side-Information Decoding – System Model
4.6.2 HSI-Decoding Processing Structure
4.7 Hierarchical Network Code Map
4.7.1 Linear HNC Map Designs
4.7.2 HNC Maps for Linear Isomorphic Layered NCM
5 WPNC in Cloud Communications
5.1 Introduction
5.2 Hierarchical Structure and Stages of Wireless Cloud
5.2.1 Hierarchical Network Transfer Function
5.2.2 Half-Duplex Constrained Stage Scheduling
5.3 Information-Theoretic Limits
5.3.1 Information-Theoretic Assessment of WPNC
5.3.2 Information-Theoretic System Model
5.3.3 Cut-Set Bound for Multicast Network
5.4 Noisy Network Coding
5.4.1 Core Principle
5.4.2 Block Structure
5.4.3 Transmission Step Codebooks and Encoding
5.4.4 Compression Step Codebooks and Encoding
5.4.5 Node Block Relay Processing
5.4.6 Final Destination Decoding
5.4.7 Achievable Rates
5.4.8 Equivalent Model
5.4.9 Noisy Network Coding in the Perspective of WPNC
5.5 Gaussian Networks
5.5.1 Gaussian Networks
5.5.2 Cut-Set Bound for Multicast Gaussian Network
5.5.3 NNC Achievable Rates for Gaussian Network
5.5.4 Examples
5.6 Compute and Forward
5.6.1 Core Principle
5.6.2 Simplified Motivation Example
5.6.3 Nested Lattice Codebooks for H-MAC
5.6.4 H-Codeword with Complex Integer Linear HNC Map
5.6.5 Hierarchical Euclidean Lattice Decoding
5.6.6 Equivalent Hierarchical Modulo Lattice Channel
5.6.7 Optimized Single-Tap Linear MMSE Equalizer
5.6.8 Achievable Computation Rate
5.6.9 Special Cases
5.6.10 Multiple Relays
5.6.11 Compute and Forward in the Perspective of WPNC
5.6.12 Examples
5.7 Hierarchical Decode and Forward in Single-Stage H-MAC
5.7.1 System Model
5.7.2 HDF Decoding
5.7.3 Joint-Metric Hierarchical Decoding on Product Codebook
5.7.4 Layered Hierarchical Decoding for Isomorphic Layered NCM
5.7.5 Properties of Hierarchical Mutual Information
5.7.6 HDF Coding Converse Rate
5.7.7 Hierarchical Capacity
5.7.8 Finite Alphabet Regular Layered NCM in Linear Memoryless Gaussian Channel
5.8 End-to-End Solvability
5.8.1 Global Linear HNC Map
5.8.2 Solvability of Linear HNC Map
5.8.3 Solving Linear Ring-Based HNC Maps
5.8.4 H-Processing Operations
Part III Design of Source, Relay, and Destination Strategies
6 NCM and Hierarchical Decoding Design for H-MAC
6.1 Introduction
6.2 NCM with HNC Maps Adapted to Channel Parameters
6.2.1 System Model
6.2.2 H-Decoding
6.2.3 Channel Optimized HNC Maps
6.3 Layered NCM and Layered H-Decoding Design
6.3.1 System Model
6.3.2 Linear Isomorphic Layered NCM
6.3.3 H-Decoding
6.3.4 Linear HNC Maps on Extended GF
6.3.5 H-Coding Rates
7 NCM Design and Processing for Parametric Channels
7.1 Introduction
7.2 Synchronization and Pilot Design
7.2.1 Synchronization and Channel State Estimation in WPNC Context
7.2.2 Fundamental Limits for Phase and Magnitude Estimators in Linear AWGN H-MAC
7.2.3 Channel State Estimators for Linear AWGN H-MAC
7.3 NCM in Frequency Selective H-MAC Channel
7.3.1 Block-Constant Frequency Selective H-MAC Channel
7.3.2 NCM with OFDM Waveform
7.4 NCM Design for Parametric Channels
7.4.1 Parameter Invariant and Uniformly Most Powerful Design
7.4.2 H-Distance Criterion Parametric Design
7.4.3 Tx-Based Adaptation and Diversity-Based Solutions
8 NCM Design for Partial HSI and Asymmetric H-MAC
8.1 Introduction
8.2 NCM for Multi-Map H-MAC
8.2.1 Design Goals
8.2.2 Structured NCM for Multi-Map H-MAC
8.2.3 Achievable H-rate Region for Multi-Map H-MAC
8.3 Structured NCM Design
8.3.1 Layered Block-Structured NCM
8.3.2 Layered Superposition-Structured NCM
8.3.3 CF-Based Superposition-Structured NCM
9 Joint Hierarchical Interference Processing
9.1 Introduction
9.2 Joint Hierarchical Interference Processing
9.3 Joint Hierarchical Interference Processing in CF-Based NCM
9.3.1 Integer-Constrained H-Ifc Cancellation
9.3.2 Successive Nulling of HNC Map Coefficients
9.3.3 Joint Hierarchical Successive CF Decoding
9.3.4 H-SCFD with Decoupled Coefficient Optimization
9.4 Joint Hierarchical Interference Cancellation for Isomorphic Layered NCM
9.4.1 Equivalent Hierarchical Channel with Joint H-Ifc Cancellation
9.4.2 Achievable H-rate with H-Ifc Cancellation
9.4.3 Conditional Regularity for Linear GF HNC Maps
10 WPNC in Complex Stochastic Networks
10.1 Principles of Wireless Cloud Coding
10.2 Wireless Cloud-Coding-Based Design of NCM
10.2.1 Random Channel Class H-MAC and Joint HNC Map
10.2.2 Coding Theorems for WCC NCM
10.3 Clustered, Nested, and Modular Cloud Framework
10.3.1 Clustered Cloud
10.3.2 Nested Cloud
10.3.3 Modular Cloud Framework
Appendix A Background Theory and Selected Fundamentals
A.1 Basic Mathematical Definitions
A.2 Linear Algebra
A.2.1 Algebraic Structures
A.2.2 Matrix Analysis
A.2.3 Miscellaneous
A.3 Detection, Decoding, and Estimation Theory
A.3.1 Bayesian Estimators
A.3.2 Maximum Likelihood Estimator
A.3.3 MAP Sequence and Symbol Decoding
A.3.4 Pairwise Error Union Upper Bound
A.3.5 Complex-Valued Optimization
A.3.6 Cramer–Rao Lower Bound
A.3.7 Sufficient Statistic
A.4 Information Theory
A.4.1 Basic Concepts
A.4.2 Capacity Region and Bounds
A.5 Lattice Coding
A.5.1 Lattices
A.5.2 Lattice Coding
References
Index


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