l0-范数约束的稀疏多径信道RLS常模盲均衡算法

摘要

针对稀疏多径信道下MPSK信号的快速盲均衡问题,提出了一种l0-范数约束的递归最小二乘常模盲均衡算法.该算法借鉴传统的递归最小二乘常模盲均衡算法思想,结合稀疏自适应滤波理论,首先利用l0-范数对均衡器抽头系数进行稀疏性约束,构造出一种l0-范数约束的加权最小二乘误差代价函数,然后依据递归最小二乘算法推导出均衡器抽头系数更新公式.该算法发挥递归最小二乘常模算法收敛速度快的优势,并对幅度极小系数附加零点吸引调整,从而实现不同幅度抽头系数的快速收敛.理论分析与仿真结果表明,与现有算法相比,该算法在保证较低剩余符号间干扰的前提下,能有效提高均衡器的收敛速度.%A novel blind equalization approach called l0-norm constraint recursive least square constant module algorithm is proposed for MPSK signal in sparse multipath channel.Firstly,motivated by the traditional recursive least square constant module algorithm and sparse adaptive filter theory,a new exponential weighting based least mean square error cost function with the l0-norm penalty on the equalizer tap coefficients is constructed.Then,the iterative updating formula of the equalizer is derived according to the recursive least square algorithm.The algorithm takes the advantages of the recursive least square algorithm,as well as attracting the inactive taps to zero,to realize fast convergence of various tap coefficients.Theoretical analysis and simulation results show that the proposed algorithm outperforms the existing algorithms in increasing the convergence rate at the same residual inter-symbol interference level.