基于最低误码率准则及Volterra序列的几何特征均衡器

针对通信系统中带内噪声及干扰的滤波问题,提出一种基于最低误码率准则的非线性几何特征均衡器.考虑到噪声与干扰具有不同的统计特性,本文所建立的均衡模型把匹配滤波器输出映射到特征空间,使信号与干扰在特征空间形成不同的几何特征,再用Volterra序列予以分离,而分离是基于最低误码率准则.仿真表明:对于扩展的二元相移键控信号,在相对强的调频信号、调幅信号及噪声的联合干扰下,匹配滤波器和基于最小均方误差准则的线性均衡器均已失效,而几何特征均衡器仍能表现出良好的性能,并且基于奇次三阶Volterra序列的几何特征均衡器更具实用价值.

Geometric Feature Equalizers Based On Minimum Bit Error Rate Criterion and Volterra Series

A novel nonlinear geometric feature equalizer adopting minimum bit error rate principle is proposed in this paper for the filtering of noise and interference whose frequency band overlaps with the desired signal in communications. Considering that the noise and the interference have different stochastic character,the proposed equalization algorithm of this paper is to map the output signal of the matched filter into feature spaces,in which the interference and the desired signal have different geometric features,and the de- sired information is recovered by Voherra series based on minimum bit error rate principle. Simulation results show that when extended binary phase shifting keying signals are contaminated by the mix of white Gaussian noise and relatively strong interference signals of am- plitude modulation and frequency modulation,the performance of matched filters and linear equalizers based on minimum mean square error principle degenerate rapidly,but geometric feature equalizers provide very low bit error rate. Furthermore,it is found that odd and third-order Voherra equalizers are more practical than the higher order Volterra equalizers.