Performance Analysis of Raptor Codes under Maximum Likelihood Decoding

Peng Wang; Guoqiang Mao; Zihuai Lin; Ming Ding; Weifa Liang; Xiaohu Ge; Zhiyun Lin

doi:10.1109/TCOMM.2016.2522403

Performance Analysis of Raptor Codes under Maximum Likelihood Decoding

Peng Wang, Guoqiang Mao, Zihuai Lin, Ming Ding, Weifa Liang, Xiaohu Ge^*, Zhiyun Lin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

In this paper, we analyze the maximum likelihood decoding performance of Raptor codes with a systematic low-density generator-matrix code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds on the decoding failure probability. The accuracy of our analysis is validated through simulations. Results of extensive Monte Carlo simulations demonstrate that for Raptor codes with different degree distributions and pre-codes, the bounds obtained in this paper are of high accuracy. The derived bounds can be used to design near-optimum Raptor codes with short and moderate lengths.

Original language	English
Article number	7393818
Pages (from-to)	906-917
Number of pages	12
Journal	IEEE Transactions on Communications
Volume	64
Issue number	3
DOIs	https://doi.org/10.1109/TCOMM.2016.2522403
Publication status	Published - Mar 2016

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title = "Performance Analysis of Raptor Codes under Maximum Likelihood Decoding",

abstract = "In this paper, we analyze the maximum likelihood decoding performance of Raptor codes with a systematic low-density generator-matrix code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds on the decoding failure probability. The accuracy of our analysis is validated through simulations. Results of extensive Monte Carlo simulations demonstrate that for Raptor codes with different degree distributions and pre-codes, the bounds obtained in this paper are of high accuracy. The derived bounds can be used to design near-optimum Raptor codes with short and moderate lengths.",

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author = "Peng Wang and Guoqiang Mao and Zihuai Lin and Ming Ding and Weifa Liang and Xiaohu Ge and Zhiyun Lin",

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AU - Mao, Guoqiang

AU - Lin, Zihuai

AU - Ding, Ming

AU - Liang, Weifa

AU - Ge, Xiaohu

AU - Lin, Zhiyun

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AB - In this paper, we analyze the maximum likelihood decoding performance of Raptor codes with a systematic low-density generator-matrix code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds on the decoding failure probability. The accuracy of our analysis is validated through simulations. Results of extensive Monte Carlo simulations demonstrate that for Raptor codes with different degree distributions and pre-codes, the bounds obtained in this paper are of high accuracy. The derived bounds can be used to design near-optimum Raptor codes with short and moderate lengths.

KW - Raptor codes

KW - asymptotic analysis

KW - decoding failure probability

KW - maximum likelihood (ML) decoding

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JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

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ER -

Performance Analysis of Raptor Codes under Maximum Likelihood Decoding

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