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Guessing Random Additive Noise Decoding A Hardware Perspective 1st Ed 2023 Syed Mohsin Abbas

Name: Guessing Random Additive Noise Decoding A Hardware Perspective 1st Ed 2023 Syed Mohsin Abbas
SKU: BELL-51605368
Price: 31.00 USD
Availability: InStock
Rating: 4.1 (90 reviews)

SKU: BELL-51605368

$ 31.00 ~~$ 45.00~~ (-31%)

4.1

90 reviews

Guessing Random Additive Noise Decoding A Hardware Perspective 1st Ed 2023 Syed Mohsin Abbas instant download after payment.

Publisher: Springer

File Extension: PDF

File size: 15.16 MB

Pages: 165

Author: Syed Mohsin Abbas, Marwan Jalaleddine, Warren J. Gross

ISBN: 9783031316623, 3031316622

Language: English

Year: 2023

Edition: 1st ed. 2023

Product desciption

Guessing Random Additive Noise Decoding A Hardware Perspective 1st Ed 2023 Syed Mohsin Abbas by Syed Mohsin Abbas, Marwan Jalaleddine, Warren J. Gross 9783031316623, 3031316622 instant download after payment.

This book gives a detailed overview of a universal Maximum Likelihood (ML) decoding technique, known as Guessing Random Additive Noise Decoding (GRAND), has been introduced for short-length and high-rate linear block codes. The interest in short channel codes and the corresponding ML decoding algorithms has recently been reignited in both industry and academia due to emergence of applications with strict reliability and ultra-low latency requirements . A few of these applications include Machine-to-Machine (M2M) communication, augmented and virtual Reality, Intelligent Transportation Systems (ITS), the Internet of Things (IoTs), and Ultra-Reliable and Low Latency Communications (URLLC), which is an important use case for the 5G-NR standard.

GRAND features both soft-input and hard-input variants. Moreover, there are traditional GRAND variants that can be used with any communication channel, and specialized GRAND variants that are developed for a specific communication channel. This book presents a detailed overview of these GRAND variants and their hardware architectures.

The book is structured into four parts. Part 1 introduces linear block codes and the GRAND algorithm. Part 2 discusses the hardware architecture for traditional GRAND variants that can be applied to any underlying communication channel. Part 3 describes the hardware architectures for specialized GRAND variants developed for specific communication channels. Lastly, Part 4 provides an overview of recently proposed GRAND variants and their unique applications.

This book is ideal for researchers or engineers looking to implement high-throughput and energy-efficient hardware for GRAND, as well as seasoned academics and graduate students interested in the topic of VLSI hardware architectures. Additionally, it can serve as reading material in graduate courses covering modern error correcting codes and Maximum Likelihood decoding for short codes.