大规模MIMO系统中低复杂度的预编码改进算法

针对大规模MIMO系统中线性预编码包含复杂的大维矩阵求逆运算,从而产生较大系统开销这一问题,提出了一种低复杂度的基于区域选择初始解的RZF-GS预编码算法.该算法是在RZF预编码的基础上,用Gauss-Seidel迭代算法代替矩阵的求逆运算,并将通常的零初始解向量优化为基于区域选择初始解的向量.实验结果表明,该算法使系统整体的复杂度降低一个数量级,同时,与Neumann级数预编码和零初始解的RZF-GS预编码相比,该算法均明显加快了其收敛速率,用较少的迭代次数就能逼近经典RZF预编码的最优误码率性能.

Low-complexity improved precoding algorithm for massive MIMO systems

For massive MIMO systems,the linear precoding contains a complex large-dimensional matrix inversion operation which resulting in more system overhead,the low-complexity RZF-GS precoding algorithm based on zone-selection initial solution is proposed.Based on the RZF precoding,the improved algorithm replaces the matrix inverse operation with the Gauss-Seidel iterative algorithm and optimizes the usual zero vector initial solution into the zone-based initial solution.The simulation results show that the algorithm reduces the overall complexity by an order of magnitude,while compared with the Neumann Series precoding and RZF-GS precoding based on zero-vector initial solution,the algorithm can accelerate the convergence rate obviously and approach the optimal bit error rate performance of the classical RZF precoding by less iteration numbers.