线性受限最大似然盲多用户检测是盲多用户检测中的一类重要方法,现有的限制方法不能保证目标用户的最优解落在限制的搜索空间中,因此在理论上不能达到最优解。提出了一种新的限制方法,能保证目标用户的最优解落在限制的搜索空间中,因此保证算法收敛到目标用户。与现有方法相比,这里给出的算法结构简单,降低了运算复杂度。仿真试验表明其具有较低的误码率和较高的系统容量。 Linearly Constrained Maximum-likelihood Blind Multi-user Detection is an important method in blind multi-user detection. The existing restrictions can not guarantee that the optimal solution of the target user falls within the limited search space, and thus can not theoretically reach the maximum Excellent solution. A new restriction method is proposed to ensure that the optimal solution of the target user falls into the limited search space, so the algorithm is guaranteed to converge to the target user. Compared with the existing methods, the proposed algorithm is simple in structure and reduces the computational complexity. Simulation tests show that it has a lower error rate and higher system capacity.