Performance Analysis of Raptor Codes Under Maximum Likelihood Decoding

—In this paper, we analyze the maximum likelihood decoding performance of Raptor codes with a systematic lowdensity 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 precodes, 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.

• Type: Journal
• Year: 2016
• Where: TCOM
• Authors: Peng Wang, Guoqiang Mao, Zihuai Lin, Ming Ding, Weifa Liang, Xiaohu Ge, Zhiyun Lin
• Keywords: Software Engineering, TCOM 2016