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) ...
Read More
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.
Read Less
Add this copy of Guessing Random Additive Noise Decoding: A Hardware to cart. $183.85, new condition, Sold by GreatBookPricesUK5 rated 4.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2023 by Springer International Publishing AG.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. XIV, 151 p. 114 illus., 101 illus. in color. Intended for professional and scholarly audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Guessing Random Additive Noise Decoding: A Hardware to cart. $168.69, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2023 by Springer International Publishing AG.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. XIV, 151 p. 114 illus., 101 illus. in color. Intended for professional and scholarly audience.
Add this copy of Guessing Random Additive Noise Decoding: A Hardware to cart. $166.68, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2023 by Springer International Publishing AG.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. XIV, 151 p. 114 illus., 101 illus. in color. Intended for professional and scholarly audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
