基于子空间的线性约束最小二乘恒模算法

线性约束最小二乘恒模算法能够有效克服恒模算法中存在的干扰捕获问题，然而，在实际的系统中，由于受到来自噪声子空间分量的影响，从而导致性能下降。针对这一问题，该文提出了一种基于子空间方法的线性约束最小二乘恒模(SLSCM)多用户检测算法并对其性能进行了理论分析。该算法收敛速度快，信道跟踪能力强，有较好的输出信干噪比和误码率性能。理论分析和仿真实验验证了该文算法的有效性和优越性。

A Linearly Constrained LSCM Algorithm Based on Subspace

Linearly constrained Least Square Constant Modulus Algorithm (LSCMA) is an effective solution to the problem of interference capture in Constant Modulus Algorithm (CMA). But the performance will degrade when it is affected by the noise subspace in practical situations. In order to overcome this shortage, a subspace-based linearly constrained LSCMA multiuser detection algorithm is proposed. The proposed algorithm offers fast convergence rate, has good channel tracking ability and provides excellent output Signal-to-Interference-plus- Noise-Ratio (SINR) and Bit Error Rate (BER) performance. Theory analysis and simulation results demonstrate the effectiveness and superiority of the proposed algorithm.