標題: Sparse Degrees Analysis for LT Codes Optimization
作者: Tsai, Pei-Chuan
Chen, Chih-Ming
Chen, Ying-ping
資訊工程學系
Department of Computer Science
公開日期: 2012
摘要: Luby Transform (LT) codes are a new member in the family of forward error correction codes without a fixed code rate. The property called rateless is attractive to researchers in last decade, and lots of studies have been proposed and attempted to improve the performance of LT codes. One variation is the use of a sparse degree distribution instead of a full one referred to in the encoding process of LT codes to reduce the search space. Observing a fact that the ability of a sparse degree distribution is limited by the nonempty degrees, we introduce a tag selection scheme to choose reasonable sparse degrees for LT codes in this paper. We firstly investigate the influence of different degrees on the error rate of LT codes and then propose a general selection algorithm based on our observations. After that, the covariance matrix adaptation evolution strategy (CMA-ES) is applied to find the optimal sparse degree distributions of which the degrees are defined by our selection algorithm. Finally, the experimental results are presented as evidence to show the proposed scheme is effective and practical.
URI: http://hdl.handle.net/11536/20975
ISBN: 978-1-4673-1509-8
期刊: 2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
顯示於類別:會議論文