摘要
针对目前已有的基于盲信号分离的盲均衡算法没有利用传输信号本身的统计特性而存在的因为近似处理引起的误差的问题,该文提出一种基于盲信号分离的自然梯度盲均衡算法。该算法充分利用了信号星座图的先验知识,为解决多峰值引起的问题采用了多阶聚类的方法。这比仅仅基于盲信号分离的盲均衡算法更为精确,从而能得到更快的收敛速度和更低的码间干扰。
Where the approximate processing leads error problems. In this paper, a new natural gradient blind equalization algorithm based on BSS is proposed. The underlying prior knowledge of source signals constellation is made full use of and a multi-stage clustering method is adopted to solve multi-peak problem in the new algorithm. Simulation results show that the new algorithm has higher accuracy than those only based on BBS and has higher convergence speed and less inter-symbol interference.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2008年第2期181-183,共3页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(60505005)
广东省自然科学基金(05103553)
关键词
盲均衡
盲分离
聚类
blind equalization
blind signal separation
clustering
