简化的复数非圆信号广义线性盲均衡算法

A Reduced Complexity Widely Linear Blind Equalization Algorithm for Complex Noncircular Signals

  • 摘要: 为了提高复数非圆信号的盲均衡性能,本文深入分析广义线性滤波理论,利用常模准则的简便性和稳健性,针对低阶复数非圆信号构造了简化的广义线性盲均衡器,并提出了一种简化的广义线性递归最小二乘常模盲均衡算法。简化的广义线性盲均衡器直接利用接收信号的实部和虚部作为均衡器输入,从而得到接收信号完整的实部和虚部的二阶统计量信息。新算法将标准的广义线性均衡算法的复数运算变成实数运算,有效地降低了标准广义线性均衡器的复杂度。仿真实验结果表明,与传统常模盲均衡算法相比,新算法在不提高计算复杂度的基础上,能够有效降低剩余码间干扰和误码率。

     

    Abstract: To improve the blind equalization performance for complex noncircular signals, the widely linear (WL) filtering theory is deeply analyzed. The paper takes advantage of simplicity and robustness of the constant modulus (CM) criterion to construct the reduced complexity widely linear blind equalizer. A reduced complexity widely linear recursive least mean square CM blind equalization algorithm is produced. The new algorithm directly uses the real and imaginary parts of received signals as input of the equalizer, thus obtains the full second-order information of the real and imaginary parts. The proposed scheme takes the real operation instead of complex operation and obtains the computational complexity which is just a few more than the traditional linear blind equalization algorithm and much less than the standard WL filter. Simulation results show that the new algorithm can simultaneously decrease the residual inter-symbol interference (ISI) and symbol error rate when compared with the traditional blind equalization algorithms.

     

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