Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform

The parameter identification of channel codes plays a significant role in the fields of adaptive modulation and coding (AMC) as well as non-cooperative communications. In this paper, an algorithm based on probability statistics and Galois field Fourier transform (PS-GFFT) is proposed to identify the...

Full description

Bibliographic Details
Main Authors: Pengtao Liu, Zhipeng Pan, Jing Lei
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8666633/
_version_ 1818323618738733056
author Pengtao Liu
Zhipeng Pan
Jing Lei
author_facet Pengtao Liu
Zhipeng Pan
Jing Lei
author_sort Pengtao Liu
collection DOAJ
description The parameter identification of channel codes plays a significant role in the fields of adaptive modulation and coding (AMC) as well as non-cooperative communications. In this paper, an algorithm based on probability statistics and Galois field Fourier transform (PS-GFFT) is proposed to identify the parameters of the Reed-Solomon (RS) codes. A threshold obtained by the probability statistics is used to skip wrong parameters within a candidate set, while GFFT is applied to reduce the error identification probability. Meanwhile, the upper bound on correct recognition rate of RS codes has been derived and proved, which quantifies the influence of the received codewords' length, the bit-error-rate of codewords, and the number of bits per symbol on the accuracy of parameters estimation. To the best of our knowledge, the upper bound, which is of great significance in evaluating the performance of recognition algorithms, is provided in this paper for the first time. The numerous simulation results illustrate that the proposed algorithm has better recognition performance than the existing RS codes recognition algorithms. Specifically, the correct recognition probability of the RS codes whose length is no more than 255 can be over 90% when the bit error rate of codewords is below 3 * 10<sup>-3</sup>, while the conventional algorithms have the best correct recognition probability of 10%. Furthermore, it is observed that the correct recognition rate of our proposed algorithm is close to the derived upper bound, especially for long code length, which further verifies the superiority of our proposed algorithm.
first_indexed 2024-12-13T11:15:34Z
format Article
id doaj.art-ca8b0264c6d1425481baac8f283bb149
institution Directory Open Access Journal
issn 2169-3536
language English
last_indexed 2024-12-13T11:15:34Z
publishDate 2019-01-01
publisher IEEE
record_format Article
series IEEE Access
spelling doaj.art-ca8b0264c6d1425481baac8f283bb1492022-12-21T23:48:37ZengIEEEIEEE Access2169-35362019-01-017336193363010.1109/ACCESS.2019.29047188666633Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier TransformPengtao Liu0https://orcid.org/0000-0002-7027-7828Zhipeng Pan1https://orcid.org/0000-0003-4577-7705Jing Lei2https://orcid.org/0000-0002-5838-5826School of Electronic Science, National University of Defense Technology, Changsha, ChinaSchool of Electronic Science, National University of Defense Technology, Changsha, ChinaSchool of Electronic Science, National University of Defense Technology, Changsha, ChinaThe parameter identification of channel codes plays a significant role in the fields of adaptive modulation and coding (AMC) as well as non-cooperative communications. In this paper, an algorithm based on probability statistics and Galois field Fourier transform (PS-GFFT) is proposed to identify the parameters of the Reed-Solomon (RS) codes. A threshold obtained by the probability statistics is used to skip wrong parameters within a candidate set, while GFFT is applied to reduce the error identification probability. Meanwhile, the upper bound on correct recognition rate of RS codes has been derived and proved, which quantifies the influence of the received codewords' length, the bit-error-rate of codewords, and the number of bits per symbol on the accuracy of parameters estimation. To the best of our knowledge, the upper bound, which is of great significance in evaluating the performance of recognition algorithms, is provided in this paper for the first time. The numerous simulation results illustrate that the proposed algorithm has better recognition performance than the existing RS codes recognition algorithms. Specifically, the correct recognition probability of the RS codes whose length is no more than 255 can be over 90% when the bit error rate of codewords is below 3 * 10<sup>-3</sup>, while the conventional algorithms have the best correct recognition probability of 10%. Furthermore, it is observed that the correct recognition rate of our proposed algorithm is close to the derived upper bound, especially for long code length, which further verifies the superiority of our proposed algorithm.https://ieeexplore.ieee.org/document/8666633/Blind recognitionReed-Solomon codesprobability statisticsGalois field Fourier transform
spellingShingle Pengtao Liu
Zhipeng Pan
Jing Lei
Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform
IEEE Access
Blind recognition
Reed-Solomon codes
probability statistics
Galois field Fourier transform
title Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform
title_full Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform
title_fullStr Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform
title_full_unstemmed Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform
title_short Parameter Identification of Reed-Solomon Codes Based on Probability Statistics and Galois Field Fourier Transform
title_sort parameter identification of reed solomon codes based on probability statistics and galois field fourier transform
topic Blind recognition
Reed-Solomon codes
probability statistics
Galois field Fourier transform
url https://ieeexplore.ieee.org/document/8666633/
work_keys_str_mv AT pengtaoliu parameteridentificationofreedsolomoncodesbasedonprobabilitystatisticsandgaloisfieldfouriertransform
AT zhipengpan parameteridentificationofreedsolomoncodesbasedonprobabilitystatisticsandgaloisfieldfouriertransform
AT jinglei parameteridentificationofreedsolomoncodesbasedonprobabilitystatisticsandgaloisfieldfouriertransform