Proceedings Article10.1109/NEWCAS.2012.6328942
Stochastic chase decoder for reed-solomon codes
Romain Heloir,Camille Leroux,Saied Hemati,Matthieu Arzel,Warren J. Gross +4 more
- 17 Jun 2012
- pp 5-8
12
TL;DR: This paper presents a hardware implementation of a soft-decision Reed-Solomon (RS) decoder, based on the stochastic Chase algorithm, which achieves a coding gain of at least 0.45 dB at FER=10-4 for the well-known RS(255,239) code.
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Abstract: This paper presents a hardware implementation of a soft-decision Reed-Solomon (RS) decoder, based on the stochastic Chase algorithm. This decoder achieves a coding gain of at least 0.45 dB at FER=10−4 for the well-known RS(255,239) code. To the best of our knowledge this is the highest reported coding gain for a hardware implementation of soft-decision RS(255,239) decoder. The decoder is implemented on a Virtex-5 FPGA and works at 800 Mb/s. The proposed decoder has a flexible architecture and is well suited for applications requiring different throughputs and decoding performance.
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Citations
Guessing random additive noise decoding with soft detection symbol reliability information - SGRAND
Ken R. Duffy,Muriel Medard +1 more
- 07 Jul 2019
TL;DR: In this article, the authors proposed a soft-GRAND (SGRAND) algorithm, which incorporates soft detection symbol reliability information and identifies a maximum likelihood decoding for arbitrary code-books.
•Posted Content
Guessing random additive noise decoding with soft detection symbol reliability information (SGRAND)
Ken R. Duffy,Muriel Medard +1 more
- 11 Feb 2019
TL;DR: SGRAND inherits desirable properties of GRAND, including being capacity achieving when used with random code-books, and having a complexity that reduces as the code-rate increases.
8
•Dissertation
Algorithm and VLSI Architecture for Polar Codes Decoder
Bo Yuan
- 01 Jul 2015
TL;DR: This dissertation presents a meta-modelling system that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of systematically cataloging and cataloging individual neurons in the brain.
4
Stochastic Computing based BCH Decoder for WBAN Systems
Kaining Han,Junchao Wang,Warren J. Gross +2 more
- 01 Aug 2018
TL;DR: A stochastic computing based soft decision decoder is presented for the BCH code defined in the IEEE 802.15.6 standard, which has the advantages of energy consumption and hardware cost while approaching the decoding performance in terms of block error rate (BLER) compared to existing BCHsoft decision decoders.
4
Advanced hardware architecture for soft decoding Reed-Solomon codes
Stefan Scholl,Norbert Wehn +1 more
- 13 Nov 2014
TL;DR: An advanced architecture based on information set decoding for processing soft information that features efficient order-2 reprocessing and handling of multiple information sets for Reed-Solomon codes is proposed.
3
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Improved decoding of Reed-Solomon and algebraic-geometry codes
Venkatesan Guruswami,Madhu Sudan +1 more
TL;DR: An improved list decoding algorithm for decoding Reed-Solomon codes and alternant codes and algebraic-geometry codes is presented and a solution to a weighted curve-fitting problem is presented, which may be of use in soft-decision decoding algorithms for Reed- Solomon codes.
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Decoding of Reed Solomon Codes beyond the Error-Correction Bound
TL;DR: To the best of the knowledge, this is the first efficient (i.e., polynomial time bounded) algorithm which provides error recovery capability beyond the error-correction bound of a code for any efficient code.
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Algebraic soft-decision decoding of Reed-Solomon codes
R. Koetter,Alexander Vardy +1 more
- 26 Oct 2000
TL;DR: A polynomial-time soft-decision decoding algorithm for Reed-Solomon codes is developed and it is shown that the asymptotic performance can be approached as closely as desired with a list size that does not depend on the length of the code.
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