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.
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.
1. Introduction.
2. Wireless Network Coded Systems for Multiple Interpretations.
3. Distributed Network Coded Modulation Schemes for Multiple Access Relay Channels.
4. Lattice Network Coding for Multi-Way Relaying Systems.
5. Nested LDGM-based Lattice Network Codes for Multi-Access Relaying Systems.
6. Design of Soft Network Coding for Two-Way Relay Channels.
7. Linear Neighbor Network Coding.
8. Random Neighbor Network Coding.
Zihuai Lin received the Ph.D. degree in Electrical Engineering from Chalmers University of Technology, Sweden, in 2006. Prior to this he has held positions at Ericsson Research, Stockholm, Sweden. Following Ph.D. graduation, he worked as a Research Associate Professor at Aalborg University, Denmark. At the same time, he worked at the Nokia Siemens Networks research center as an external senior researcher on 4G LTE standardization. He is currently a senior lecturer at the School of Electrical and Information Engineering, the University of Sydney, Australia. He has published more than 200 papers in international conferences and journals, which have been cited more than 2500 times. He holds twelve CN, three US, and one AU patents on LTE system design, distributed network coding and wireless sensor networks, microwave Ghost imaging, indoor localization, and ECG/EEG AI data analysis. His research interests include source/channel/network coding, coded modulation, massive MIMO, mmWave/THz communications, radio resource management, cooperative communications, small-cell networks, 5G/6G, IoT, wireless Artificial Intelligence (AI), ECG and EEG AI signal analysis, Radar imaging, etc.
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