This book provides a consolidated view of the various network coding techniques to be implemented at the design of the wireless networks for improving its overall performance. It covers multiple sources communicating with multiple destinations via a common relay followed by network coded modulation schemes for multiple access relay channels. Performance of the distributed systems based on distributed convolutional codes with network coded modulation is covered including a two-way relay channel (TWRC). Two MIF protocols are proposed including derivation of signal-to-noise ratio (SNR) and development of threshold of the channel conditions of both.
Features:
- Systematically investigates coding and modulation for wireless relay networks.
- Discusses how to apply lattice codes in implementing lossless communications and lossy source coding over a network.
- Focusses on theoretical approach for performance optimization.
- Includes various network coding strategies for different networks.
- Reviews relevant existing and ongoing research in optimization along with practical code design.
This book aims at Researchers, Professionals and Graduate students in Networking, Communications, Information, Coding Theory, Theoretical Computer Science, Performance Analysis and Resource Optimization, Applied Discrete Mathematics, and Applied Probability.
Author(s): Zihuai Lin
Publisher: CRC Press
Year: 2022
Language: English
Pages: 165
City: Boca Raton
Cover
Half Title
Title Page
Copyright Page
Contents
List of Figures
List of Tables
Acknowledgments
Acronyms
Author Biography
Chapter 1: Introduction
1.1. Physical Layer Lattice Network Coding and Soft Information Delivery
1.1.1. Lattice Coding
1.1.2. PNC soft Information and delivery
1.2. Network Layer Network Coding schemes
1.2.1. XOR network Coding
1.2.2. Linear network Coding
1.2.2.1. Random linear network Coding
1.2.2.2. Distributed random linear network coding
1.2.3. Benefits made by network coding
1.2.3.1. Bandwidth efficiency
1.2.3.2. The basic idea
1.2.3.3. Other traffic configurations
1.2.3.4. Undirected networks
1.2.4. Energy efficiency
1.2.4.1. Multicast
1.2.4.2. Other traffic configurations
1.2.5. Delay performance
1.2.5.1. The average delay
1.2.5.2. Delay Distribution
1.2.6. Reliability
1.2.6.1. Retransmissions and network coding
1.2.6.2. Combination of routing and network coding
1.3. Network coding design challenges
1.4. Organization of the Book
Chapter 2: Wireless Network Coded Systems for Multiple Interpretations
2.1. Introduction
2.2. System Model
2.3. Optimization Formulation
2.4. Analysis of the Average Channel Capacity
2.5. Network Coded System based on Nested Codes
2.5.1. Soft-Decision Decoding with Nested Codes
2.6. Analytical Bounds on the Bit Error Probability
2.7. Code Search
2.8. Numerical and Simulation Results
2.8.1. Average Channel Capacity and Outage Probability
2.8.2. The Performance of OS
2.8.3. The Performance of Nested Codes
2.9. Conclusions
Chapter 3: Distributed Network Coded Modulation Schemes for Multiple Access Relay Channels
3.1. Introduction
3.2. System Model
3.3. Distributed Network Coded Modulation Schemes based
on Punctured Convolutional Codes
3.3.1. Decoding With Network Coded Modulation at the Destination Node
3.3.2. Analytical bounds on the bit error probability for the multiple access relay channels
3.4. Interleaved Distributed Network Coded Systems
3.5. Simulation Results for Distributed Network Coded Systems
3.5.1. Simulation results for Distributed Network Coded System without Interleaver
3.5.2. Simulation results for Interleaved Distributed Network Coded System
3.6. Summary
Chapter 4: Lattice Network Coding for Multi-Way Relaying Systems
4.1. Introduction
4.2. System Model
4.2.1. System Model
4.2.2. Nested Convolutional Codes and Lattice Network Coding
4.3. Nested Convolutional Lattice Network Codes
4.4. Performance Analysis
4.5. Numerical Simulation Results
4.6. Conclusion
Chapter 5: Nested LDGM-based Lattice Network Codes for Multi-Access Relaying Systems
5.1. Introduction
5.2. System Model
5.3. Coding Process: Nested Binary LDGM Codes
5.4. Coding Process: Nested Non-binary LDGM with Lattice
5.5. L-EMS Decoding Algorithm
5.6. Performance Analysis
5.7. Code Optimization Using Lattice based Monte Carlo Method
5.8. Numerical and Simulation Results
5.8.1. Lattice Settings
5.8.2. Lattice-based Monte Carlo Method
5.8.3. Performance for the Lattice-based EMS decoder
5.8.4. Performance of the nested non-binary LDGM codes with lattice
5.9. Conclusion
Chapter 6: Design of Soft Network Coding for Two-Way Relay Channels
6.1. Introduction
6.2. System Model
6.3. TCQ Codebook Design
6.4. Performance Analysis
6.4.1. Set a threshold
6.4.2. Performance Analysis on the Two Schemes
6.5. Simulation Results
6.6. Conclusion
Chapter 7: Linear Neighbor Network Coding
7.1. Introduction
7.2. System Model
7.3. Theoretical Analysis
7.3.1. Construction of the States
7.3.2. Transition Matrices
7.3.3. The State Vectors
7.3.4. Reliability
7.3.5. Networks without Network Coding
7.4. Bounds on the Reliability
7.4.1. The Upper Bound
7.4.2. The Lower Bound
7.5. Results and Discussion
7.6. Conclusions
Chapter 8: Random Neighbor Network Coding
8.1. Introduction
8.2. System model
8.3. Theoretical analysis
8.3.1. States
8.3.2. Transition matrices
8.3.3. Probability Vector and the reliability
8.4. Optimisations
8.4.1. Optimize the reliability at an individual round
8.4.2. Optimize the expected round to absorb
8.5. Numerical results
8.5.1. Validation of the theoretical analysis
8.5.2. Optimal Selection of the tuning Parameter
8.5.3. Examination on the reliability gain
8.5.4. Comparison with the random linear network coding scheme
8.6. Summary
Index
