鲁棒约束最小二乘恒模算法

在实际的通信环境中,信号方向向量偏差使得线性约束最小二乘恒模算法的性能急剧下降.针对这一问题,提出了鲁棒约束最小二乘恒模算法.该算法通过在代价函数中增加一个方向向量存在偏差的模值约束条件来提高算法的鲁棒性,并在此约束条件下推导出权重向量的递推公式.另外,采用递推算法计算逆矩阵,大大地降低了计算复杂度.所提算法对信号方向向量偏差具有较强的鲁棒性,从而保证了阵列输出的信干噪比接近最优值.仿真实验结果表明,与传统算法相比,所提鲁棒约束最小二乘恒模算法具有更好的性能,且能适应实际复杂的通信环境.

Robust Constrained Least Squares Constant Modulus Algorithm

During the actual communication practice, the performance of linearly constrained least squares constant modulus algorithm (LC-LSCMA) will deteriorate acutely due to signal steering vector mismatches. A novel approach, i.e., the robust constrained LSCMA, is therefore proposed the way the recursion formula of weight vector is deduced under the condition that the modulus involving mismatched directional vector is constrained and the condition is included in the cost function so as to improve the robustness of LSCMA. Besides, the complexity of computation can be reduced by introducing the recursive algorithm to compute the inverse matrix. The robust constrained LSCMA provides a high robustness against signal steering vector mismatches, thus enabling the SINR of array output to approximate to its optimal value. Simulation results show that the performance of the proposed algorithm is superior to the conventional algorithm and more adaptable to the actual complex communication.