@inproceedings{e43be9ad0a7f4981afa9c5f7d7126044,
title = "Bounds on the finite-length raptorq codes under maximum likelihood decoding",
abstract = "In this paper, we analysis the maximum likelihood (ML) decoding failure probability (DFP) of finite length RaptorQ codes with a high-order low density generator-matrix (LDGM) code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds of DFP on the RaptorQ codes under ML decoding algorithm. Finally, we verify the accuracy of derived theoretical bounds through the Monte Carlo simulations with different degree distributions. The high accuracy bounds can be used to design near-optimum RaptorQ codes with short and moderate lengths.",
keywords = "Decoding failure probability, Massive Machine-to-Machine (mM2M) communications, Maximum likelihood decoding, RaptorQ codes",
author = "Ke Zhang and Jian Jiao and Shushi Gu and Shaohua Wu and Qinyu Zhang",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Singapore Pte Ltd.; 6th International Conference on Communications, Signal Processing, and Systems, CSPS 2017 ; Conference date: 14-07-2017 Through 16-07-2017",
year = "2019",
doi = "10.1007/978-981-10-6571-2\_101",
language = "英语",
isbn = "9789811065705",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "831--838",
editor = "Qilian Liang and Min Jia and Jiasong Mu and Wei Wang and Xuhong Feng and Baoju Zhang",
booktitle = "Communications, Signal Processing, and Systems - Proceedings of the 2017 International Conference on Communications, Signal Processing, and Systems",
address = "德国",
}