Computationally Efficient Data Detection in Massive MIMO Wireless Systems via Semi-Iterative Method

Practical data detectors must achieve low error-rate at low-complexity for massive multiple-input multiple-output (MIMO) wireless systems. Since near-optimal minimum mean square error (MMSE) detection exhibits high computational complexity for such wireless systems, various iterative methods as well as their enhanced variants have been proposed. The efficiency of iterative approaches, however, is not satisfying due to slow convergence rate and reduced accuracy. This paper proposes a novel semi-iterative data detection algorithm for massive MIMO systems that simultaneously achieves a large improvement in convergence and accuracy with respect to the corresponding iterative method. We provide a general three-term recurrence expression for semi-iterative detection and incorporate it with Richardson method as a show case. To further improve the convergence rate of the proposed technique, a new trace-diagonal based low-complexity initial method is developed. A sufficient condition for convergence of the proposed method is also provided. We analyze the associated complexity of semi-iterative detector, and provide numerical results which demonstrate that the proposed detector is superior to recently introduced iterative detectors in terms of both the error-rate performance and computational complexity.