Soft Maximum Likelihood Decoding using GRAND
Amit Solomon,Ken R. Duffy,Muriel Medard +2 more
- 07 Jun 2020
- pp 1-6
83
TL;DR: In this paper, the authors proposed a soft maximum likelihood (ML) decoder called Soft GRAND (SGRAND) that fully avails of soft detection information and is suitable for use with any arbitrary high-rate, short-length block code.
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Abstract: Maximum Likelihood (ML) decoding of forward error correction codes is known to be optimally accurate, but is not used in practice as it proves too challenging to efficiently implement. Here we propose a development of a previously described hard detection ML decoder called Guessing Random Additive Noise Decoding (GRAND). We introduce Soft GRAND (SGRAND), a ML decoder that fully avails of soft detection information and is suitable for use with any arbitrary high-rate, short-length block code. We assess SGRAND's performance on Cyclic Redundancy Check (CRC)-aided Polar (CA-Polar) codes, which will be used for all control channel communication in 5G New Radio (NR), comparing its accuracy with CRC-Aided Successive Cancellation List decoding (CA-SCL), a state-of-the-art soft-information decoder specific to CA-Polar codes.
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Citations
Ordered Reliability Bits Guessing Random Additive Noise Decoding
Ken R. Duffy
- 06 Jun 2021
TL;DR: In this paper, a soft-detection variant of Guessing Random Additive Noise Decoding (GRAND) called Ordered Reliability Bits GRAND that can decode any moderate redundancy blockcode was proposed.
74
High-Throughput VLSI Architecture for GRAND
Syed Mohsin Abbas,Thibaud Tonnellier,Furkan Ercan,Warren J. Gross +3 more
- 01 Oct 2020
TL;DR: The first hardware architecture for the GRAND algorithm is proposed and compared with a decoder tailored for a (79, 64) BCH code show that the proposed architecture can achieve a slightly higher average throughput at high SNRs, while obtaining the same decoding performance.
73
•Posted Content
Keep the bursts and ditch the interleavers
TL;DR: It is established that certain well-known structured codes are ill-suited for use in bursty channels, but Random Linear Codes (RLCs) are robust to correlated noise, which suggests that the use of RLCs with GRAND-MO is a good candidate for applications requiring high throughput with low latency.
Multi-Code Multi-Rate Universal Maximum Likelihood Decoder using GRAND
Arslan Riaz,Vaibhav Bansal,Amit Solomon,Wei An,Qijun Liu,Kevin Galligan,Ken R. Duffy,Muriel Medard,Rabia Tugce Yazicigil +8 more
- 13 Sep 2021
TL;DR: In this paper, the authors present the first fully integrated universal maximum likelihood decoder in 40 nm CMOS using the Guessing Random Additive Noise Decoding (GRAND) algorithm for low-power applications.
57
Ordered Reliability Bits Guessing Random Additive Noise Decoding
TL;DR: Ordered Reliability Bits GRAND as discussed by the authors is a soft-detection variant of Guessing Random Additive Noise Decoding (GRAND) that can accurately decode any moderate redundancy blockcode.
56
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