扩频系统中最小误码率意义下的最优干扰抑制技术

The Optimum Interference Suppression Technique in the MBER Sense for Spread Spectrum Systems

通过论证最小化误码率 (MBER) ,最小均方误差 (MMSE)以及约束最小均值输出能量 (MMOE)之间的关系 ,将MBER准则下最优干扰抑制器的设计转化为后两种准则下最优干扰抑制器的设计 ,并分别导出两种自适应算法 :递推最小二乘 (RLS)和盲递推最小二乘 (BRLS) .前者抑制干扰效果好 ,但需要期望信号 ;后者无需期望信号 ,但抑制效果较差 .本文将两种算法合理配合 ,给出了动态环境下的干扰抑制方法 .

By examining the relationship between the minimum bit error rate (MBER),minimum mean square error (MMSE) and the constrained minimum mean output energy (MMOE),we resolve the interference suppressor optimized in the MBER sense into the optimum suppressor in the MMSE criterion and the constrained MMOE criterion which lend themselves to adaptive implementation more readily than the MBER suppressor.This paper addresses the recursive least squares (RLS) algorithm and the blind RLS (BRLS) algorithm without known desire signal.The suppressed effect of the BRLS algorithm is shown to be significantly inferior to the RLS algorithm with known data sequences.This paper proposes the scheme of combining RLS with BRLS to solve the interference suppression in time-varying environment.