A Low Complexity Data Detection Scheme for Massive MIMO Systems Using the TOR Algorithm

Massive multiple-input multiple-output (MIMO) technology utilizes large antenna arrays at the base-station (BS) to support a large number of users with the same time/frequency resources. Uplink signal detection poses a significant challenge in massive MIMO systems. Although minimum-mean square-error based detectors become the mainstay of classical massive MIMO systems, they require a large-dimensional matrix inversion, which is computationally extensive. This paper proposes a new massive MIMO detector based on the two-parameter over relaxation (TOR) algorithm. The relaxation and acceleration parameters are carefully selected on the basis of the spectral radius to achieve a good balance between the performance and the complexity. Compared to existing linear detectors, the proposed TOR based detector is more stable because of its relaxation and acceleration parameters. The results show that the proposed massive MIMO detector achieves a remarkable performance gain and overall complexity reduction compared to existing detectors, particularly when the number of users is comparable to the number of BS antennas. The proposed TOR detector achieves better performance than the existing detectors when using the same number of iterations.