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This book addresses challenges faced by both the algorithm designer and the chip designer, who need to deal with the ongoing increase of algorithmic complexity and required data throughput for today’s mobile applications. The focus is on implementation aspects and implementation constraints of individual components that are needed in transceivers for current standards, such as UMTS, LTE, WiMAX and DVB-S2. The application domain is the so called outer receiver, which comprises the channel coding, interleaving stages, modulator, and multiple antenna transmission. Throughout the book, the focus is on advanced algorithms that are actually in use in modern communications systems. Their basic principles are always derived with a focus on the resulting communications and implementation performance. As a result, this book serves as a valuable reference for two, typically disparate audiences in communication systems and hardware design.
Covering the fast evolving area of advanced coding, Error Control Coding for B3G/4G Wireless Systems targets IMT-Advanced systems to present the latest findings and implementation solutions. The book begins by detailing the fundamentals of advanced coding techniques such as Coding, Decoding, Design, and Optimization. It provides not only state-of-the-art research findings in 3D Turbo-codes, non-binary LDPC Codes, Fountain, and Raptor codes, but also insights into their real-world implementation by examining hardware architecture solutions, for example VLSI complexity, FPGA, and ASIC. Furthermore, special attention is paid to Incremental redundancy techniques, which constitute a key feature o...
This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains...