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More Offers Of Store ››Codes and turbo codes
www.dealspluses.com/coupons/link.springer.comThis book is devoted to one of the essential functions of modern telecommunications systems: channel coding or error correction coding. At the crossroads of information theory, mathematics and electronics, channel coding has undergone many developments since Claude Shannon's founding work. From the simple Hamming code (1950) and LDPC codes (1962) to the more recent turbo codes (1993), channel coding has evolved considerably and has incorporated ever more sophisticated concepts, especially the probabilistic processing of information. The book's main topic is iteratively decoded algebraic codes, convolutional codes and concatenated codes, and it also presents digital modulation with which channel coding is closely associated to make up the heart of the physical layer of telecommunications systems. The most important theoretical aspects are given, and the building of codes is detailed and justified. Decoding algorithms are developed and, whenever possible, accompanied by simulation results characteristic of their correcting power. The authors are researchers and lecturers recognised for their expertise in the field of encoding and decoding algorithms and associated circuits. Codes and Turbo Codes is intended both as a means for discovering the domain, a valuable source of information about the many techniques imagined since the mid-twentieth century, and as a step towards addressing problems not yet entirely solved.
More Offers Of Store ››Turbo Codes
www.dealspluses.com/coupons/link.springer.comPREFACE The increasing demand on high data rate and quality of service in wireless communication has to cope with limited bandwidth and energy resources. More than 50 years ago, Shannon has paved the way to optimal usage of bandwidth and energy resources by bounding the spectral efficiency vs. signal to noise ratio trade-off. However, as any information theorist, Shannon told us what is the best we can do but not how to do it [1]. In this view, turbo codes are like a dream come true: they allow approaching the theoretical Shannon capacity limit very closely. However, for the designer who wants to implement these codes, at first sight they appear to be a nightmare. We came a huge step closer in striving the theoretical limit, but see the historical axiom repeated on a different scale: we know we can achieve excellent performance with turbo codes, but not how to realize this in real devices.
More Offers Of Store ››BATS Codes
www.dealspluses.com/coupons/ebooks.comThis book discusses an efficient random linear network coding scheme, called BATched Sparse code, or BATS code, which is proposed for communication through multi-hop networks with packet loss. Multi-hop wireless networks have applications in the Internet of Things (IoT), space, and under-water network communications, where the packet loss rate per network link is high, and feedbacks have long delays and are unreliable. Traditional schemes like retransmission and fountain codes are not sufficient to resolve the packet loss so that the existing communication solutions for multi-hop wireless networks have either long delay or low throughput when the network length is longer than a few hops. These issues can be resolved by employing network coding in the network, but the high computational and storage costs of such schemes prohibit their implementation in many devices, in particular, IoT devices that typically have low computational power and very limited storage. A BATS code consists of an outer code and an inner code. As a matrix generalization of a fountain code, the outer code generates a potentially unlimited number of batches, each of which consists of a certain number (called the batch size) of coded packets. The inner code comprises (random) linear network coding at the intermediate network nodes, which is applied on packets belonging to the same batch. When the batch size is 1, the outer code reduces to an LT code (or Raptor code if precode is applied), and network coding of the batches reduces to packet forwarding. BATS codes preserve the salient features of fountain codes, in particular, their rateless property and low encoding/decoding complexity. BATS codes also achieve the throughput gain of random linear network coding. This book focuses on the fundamental features and performance analysis of BATS codes, and includes some guidelines and examples on how to design a network protocol using BATS codes.
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More Offers Of Store ››Error Detecting Codes
www.dealspluses.com/coupons/link.springer.comError detecting codes are very popular for error control in practical systems for two reasons. First, such codes can be used to provide any desired reliability of communication over any noisy channel. Second, implementation is usually much simpler than for a system using error correcting codes. To consider a particular code for use in such a system, it is very important to be able to calculate or estimate the probability of undetected error. For the binary symmetric channel, the probability of undetected error can be expressed in terms of the weight distribution of the code. The first part of the book gives a detailed description of all known methods to calculate or estimate the probability of undetected error, for the binary symmetric channel in particular, but a number of other channel models are also considered. The second part of the book describes a number of protocols for feedback communication systems (ARQ systems), with methods for optimal choice of error detecting codes for the protocols. Results have been collected from many sources and given a unified presentation. The results are presented in a form which make them accessible to the telecommunication system designer as well as the coding theory researcher and student. The system designer may find the presentation of CRC codes as well as the system performance analysis techniques particularly useful. The coding theorist will find a detailed account of a part of coding theory which is usually just mentioned in most text books and which contains a number of interesting and useful results as well as many challenging open problems. Audience: Essential for students, practitioners and researchers working in communications and coding theory. An excellent text for an advanced course on the subject.
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