Consider the problem of designing capacity-achieving codes for multi-terminal communication scenarios. For point-to-point communication problems, one can optimize a single code to approach capacity, but for multi-terminal problems this translates to optimizing a single code to perform well over the entire region of channel parameters. A coding scheme is called universal if it allows reliable communication over the entire achievable region promised by information theory. It was recently shown that terminated low-density parity-check convolutional codes (also known as spatially-coupled low-density parity-check ensembles) have belief-propagation thresholds that approach their maximum a-posteriori thresholds. This phenomenon, called "threshold saturation via spatial-coupling," was proven for binary erasure channels and then for binary memoryless symmetric channels. This approach provides us with a new paradigm for constructing capacity approaching codes. It was also conjectured that the principle of spatial coupling is very general and that the phenomenon of threshold saturation applies to a very broad class of graphical models. In this work, we consider a noisy Slepian-Wolf problem (with erasure and binary symmetric channel correlation models) and the binary-input Gaussian multiple access channel, which deal with correlation between sources and interference at the receiver respectively. We derive an area theorem for the joint decoder and empirically show that threshold saturation occurs for these multi-user scenarios. We also show that the outer bound derived using the area theorem is tight for the erasure Slepian-Wolf problem and that this bound is universal for regular LDPC codes with large left degrees. As a result, we demonstrate near-universal performance for these problems using spatially-coupled coding systems.

This handbook is an authoritative, comprehensive reference on optical networks, the backbone of today’s communication and information society. The book reviews the many underlying technologies that enable the global optical communications infrastructure, but also explains current research trends targeted towards continued capacity scaling and enhanced networking flexibility in support of an unabated traffic growth fueled by ever-emerging new applications. The book is divided into four parts: Optical Subsystems for Transmission and Switching, Core Networks, Datacenter and Super-Computer Networking, and Optical Access and Wireless Networks. Each chapter is written by world-renown experts that represent academia, industry, and international government and regulatory agencies. Every chapter provides a complete picture of its field, from entry-level information to a snapshot of the respective state-of-the-art technologies to emerging research trends, providing something useful for the novice who wants to get familiar with the field to the expert who wants to get a concise view of future trends.

This book gives a review of the principles, methods and techniques of important and emerging research topics and technologies in Channel Coding, including theory, algorithms, and applications. Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its applications - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in Channel Coding - Presents core principles in Channel Coding theory and shows their applications - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge

In this book, leading authorities unify algebraic- and graph-based LDPC code designs and constructions into a single theoretical framework.

Wireless communications use different orthogonal multiple access techniques to access a radio spectrum. The need for the bandwidth efficiency and data rate enhancing increase with the tremendous growth in the number of mobile users. One promising solution to increase the data rate without increasing the bandwidth is non-orthogonal multiple access channel. For the noiseless channel like the data network, the non-orthogonal multiple access channel is named: Binary Erasure Multiple Access Channel (BEMAC). To achieve two corner points on the boundary region of the BEMAC, a half rate code is needed. One practical code which has good performance over the BEMAC is the Low Density Parity Check (LDPC) codes. The LDPC codes receive a lot of attention nowadays, due to the good performance and low decoding complexity. However, there is a tradeoff between the performance and the decoding complexity of the LDPC codes. In addition, the LDPC encoding complexity is a problem, because an LDPC code is defined with its parity check matrix which is sparse and random and lacks of structure. This thesis consists of two main parts. In the first part, we propose a new practical method to construct an irregular half LDPC code which has low encoding complexity. The constructed code supposed to have a good performance and low encoding complexity. To have a low encoding complexity, the parity check matrix of the code must have lower triangular shape. By implementing the encoder and the decoder, the performance of the code can be also evaluated. Due to the short cycles in the code and finite length of the code the actual rate of the code is degraded. To improve the actual rate of the code, the guessing algorithm is applied if the Belief Propagation is stuck. The actual rate of the code increases from 0.418 to0.44. The decoding complexity is not considered when the code is constructed.Next in the second part, a regular LDPC code is constructed which has low decoding complexity. The code is generated based on the Gallager method. We present a new method to improve the performance of an existing regular LDPC code. The proposed method does not add a high complexity to the decoder. The method uses a combination of three algorithms: 1- Standard Belief Propagation 2- Generalized tree-expected propagation 3- Guessing algorithm. The guessing algorithm is impractical when the number of guesses increases. Because the number of possibilities increases exponentially with increasing the number of guesses. A new guessing algorithm is proposed in this thesis. The new guessing algorithm reduces the number of possibilities by guessing on the variable nodes which are connected to a set of check nodes. The actual rate of the code increases from 0.41 to 0.43 after applying the proposed method and considering the number of possibilities equal to two in the new guessing algorithm.

Low-density parity-check (LDPC) codes in conjunction with iterative decoding based on message-passing algorithms have been shown to achieve excellent performance over a variety of communication channels. In this dissertation, we investigate LDPC codes under two scenarios which present different challenges for providing robust communications.