Geometric Feature Equalizers Based on Minimum Bit Error Rate Criterion and Volterra Series
Lenan Wu · Signal Processing · 2008
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.