最小误码率准则盲源分离算法

Minimum BER Criterion Based Blind Source Separation Method

针对通信信号混合的盲分离问题,结合通信系统中的误码率性能指标,本文提出一种基于最小误码率准则的盲源分离算法。本算法的基本原理是,将推导的最小误码率准则结合最大似然原则建立盲源分离代价函数,形成一种最小误码率约束的代价函数,接着借助于自然梯度下降搜索,最小化代价函数实现盲源分离。仿真实验分析表明:提出的最小误码率约束代价函数得到的盲源分离算法,比原有的最大似然原则代价函数得到的盲源分离算法,具有更好的收敛性能和分离精度。

For the blind separation of the mixtures of communication signals, in consideration of the bit error rate （BER） performance metrics in communication systems, a blind source separation （BSS） algorithm is proposed based on minimum bit error rate criterion in this paper. The basic principle of the proposed algorithm includes that： first of all, the new mini- mum bit error rate criterion constrained cost function is established according to the derived minimum bit error rate criterion incorporated into maximum likelihood （ML） principle; secondly, by virtue of nature gradient descent search, the blind separation is accomplished through minimizing this built cost function. Simulation experiments and analysis show that, in comparison with the blind separation algorithm based on the cost function of the maximum likelihood principle, the proposed algorithm based on minimum BER criterion constrained cost function can lead to better performance in speed of convergence and separation accuracy.