ScholarLens Back to search
2003•Unpublished venueRequires access

Sub-optimum decoding of Reed-Solomon codes

V. Ponnampalam, Branka Vucetic

Open publisher page 1 citations

Abstract

This paper presents a sub-optimum soft decision decoding (SDD) algorithm for Reed Solomon (RS) codes. The sub-optimum algorithm is based on a maximum likelihood (ML) algorithm. The performance of the decoding algorithm and its complexity are obtained by computer simulations and compared to some well known decoding schemes. It is shown that the proposed algorithm achieves near-ML performance with significantly lower decoding complexity.

About this research paper

What this paper is about

This paper presents a sub-optimum soft decision decoding (SDD) algorithm for Reed Solomon (RS) codes. The sub-optimum algorithm is based on a maximum likelihood (ML) algorithm. The performance of the decoding algorithm and its complexity are obtained by computer simulations and compared to some well known decoding schemes. It is shown that the proposed algorithm achieves near-ML performance with significantly lower decoding complexity.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

This paper presents a sub-optimum soft decision decoding (SDD) algorithm for Reed Solomon (RS) codes. The sub-optimum algorithm is based on a maximum likelihood (ML) algorithm. The performance of the decoding algorithm and its complexity are obtained by computer simulations and compared to some well known decoding schemes. It is shown that the proposed algorithm achieves near-ML performance with significantly lower decoding complexity.

Key concepts: Decoding methods, Berlekamp–Welch algorithm, Sequential decoding, List decoding, Algorithm, Computer science, Reed–Solomon error correction, Computational complexity theory

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Sub-optimum decoding of Reed-Solomon codes — Research Paper | ScholarLens