基于SOR-PCG的低复杂度信号检测算法研究

针对最小均方误差信号检测算法复杂度随着天线数量增加呈指数增长的问题,提出低复杂度的预处理共轭梯度信号检测算法.该算法通过灵活调整松弛因子,运用预处理技术降低矩阵条件数,从而加快共轭梯度信号检测算法的收敛速度.仿真结果显示,该算法在小数量的迭代中能够达到和最小均方误差检测算法相似的误码率,算法复杂度下降了一个数量级.通过选择适当的松弛因子,相比直接用共轭梯度法,能够更快收敛到最佳值.

Study on low-complexity signal detection based on successive over relaxation-preconditioned conjugate gradient method

In view that the complexity of the minimum mean square error signal detection algorithm grows exponentially with the number of antennas, putting forward the low complexity signal detection algorithm of preconditioning conjugate gradient. Through the flexible adjustment of relaxation factor, the algorithm using pretreatment technology to reduce the matrix condition number, so as to speed up the convergence of conjugate gradient signal detection algorithm. The simulation results show that proposed algorithm can achieves the near-optimal bit error rate performance of minimum mean square error detection algorithm with a small number of iterations, and computational complexity reduces about one order of magnitude. Compared with the conjugate gradient method, the proposed algorithm can quickly converge to the optimum value by the flexible adjustment of relaxation factor.