Abstract

In this paper, we propose a low-complexity uplink signal detection algorithm based on reactive tabu search (RTS) in massive multiple-input multiple-output (MIMO) systems. As the number of antennas increases, conventional RTS algorithm achieves near-maximum likelihood (ML) performance in massive MIMO systems. But the complexity of the initial solution vector is too high. Therefore, we propose a symmetric successive over-relaxation RTS (SSOR-RTS) algorithm which achieves the same error rate performance of RTS but with lower complexity. The key idea is to calculate the initial solution vector of RTS algorithm using the SSOR iterative method. A criterion based on ML cost change rate to limit the number of SSOR iterations is also proposed to further reduce the complexity of the RTS algorithm. Simulation results show that the SSOR-RTS and adaptive SSOR-RTS achieve almost the same performance with RTS algorithm at significantly less complexity.

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