This 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.

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This 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.

This book explains the philosophy of the polar encoding and decoding technique. Polar codes are one of the most recently discovered capacity-achieving channel codes. What sets them apart from other channel codes is the fact that polar codes are designed mathematically and their performance is mathematically proven. The book develops related fundamental concepts from information theory, such as entropy, mutual information, and channel capacity. It then explains the successive cancellation decoding logic and provides the necessary formulas, moving on to demonstrate the successive cancellation decoding operation with a tree structure. It also demonstrates the calculation of split channel capacities when polar codes are employed for binary erasure channels, and explains the mathematical formulation of successive cancellation decoding for polar codes. In closing, the book presents and proves the channel polarization theorem, before mathematically analyzing the performance of polar codes.

BUILDING CODES ILLUSTRATED STAY INFORMED OF THE LATEST UPDATES TO THE INTERNATIONAL BUILDING CODE WITH THE LEADING VISUAL REFERENCE In the newly revised Seventh Edition of Building Codes Illustrated: A Guide to Understanding the 2021 International Building CodeÂ, architectural drawing expert Francis D.K. Ching and well known architect ­Steven R. Winkel deliver a beautifully illustrated and intuitively written handbook for the 2021 International Building Code (IBC). The authors provide brand new chapters on plumbing fixture counts, elevators, special construction, and existing buildings while updating the remainder of the material to align with recent changes to the IBC. Easy to navigate and perfect as a quick-reference guide to the IBC, Building Codes Illustrated is a valuable visual resource for emerging professionals. The book also includes: Thorough introductions to navigating the Code, use and occupancy, special uses and occupancies, and building heights and areas Full explorations of the types of construction, fire resistive construction, interior finishes, fire-protection systems, and means of egress Practical discussions of accessibility, interior environment, exterior walls, roof assemblies, and structural provisions In-depth examinations of special inspections and tests, soils and foundations, building materials and systems, and elevators Perfect for students of architecture, interior design, construction, and engineering, the latest edition of Building Codes Illustrated is also ideal for professionals in these fields seeking an up-to-date reference on the 2021 International Building Code.

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