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abbas s guessing random additive noise decoding hardware perspective 2023

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Textbook in PDF format 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. Part I Guessing Random Additive Noise Decoding: Preliminaries Guessing Random Additive Noise Decoding (GRAND) Part II Hardware Architectures for Conventional GRAND Variants Hardware Architecture for GRAND with ABandonment (GRANDAB) Hardware Architecture for Ordered Reliability Bits GRAND (ORBGRAND) Hardware Architecture for List GRAND (LGRAND) Part III Hardware Architectures for Specialized GRAND Variants Hardware Architecture for GRAND Markov Order (GRAND-MO) Hardware Architecture for Fading-GRAND Part IV GRAND Extensions A Survey of Recent GRAND Variants

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Abbas S. Guessing Random Additive Noise Decoding. A Hardware Perspective 2023.pdf 15.2 MB

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abbas s guessing random additive noise decoding hardware perspective 2023

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