基于最小二乘恒模算法及子空间方法的盲多用户检测算法

The lscm algorithm and subspace approach for blind multiuser detection

恒模算法(CMA)是一种广泛应用于阵列处理、均衡、多用户检测中的盲算法。最小二乘恒模算法(LSCMA)由于其全局收敛性及稳定性受到关注,但是它在信噪比较低时性能不是很理想。本文将最小二乘恒模算法与子空间方法相结合,提出一种基于子空间分解的恒模算法,称为LSCM_SUB算法。仿真结果表明这种算法的收敛性能比LSCMA要好,尤其是在信噪比低的时候。

The constant modulus algorithm(CMA) is a blind algorithm. It is applied in the array processing、equalization and multiuser detection widely. The least square CMA is a popular CMA because of its global convergence and stability. But its performance is not superior when the SNR is low. In this paper, we combine the LSCMA with the subspace approach and propose the 慙SCM_SUB?algorithm. Simulation results show that the proposed LSCM_SUB algorithm is superior to the LSCMA especially in the low SNR.