Efficient Nonlinear Precoding for Massive MIMO Downlink Systems With 1-Bit DACs

Abstract

The power consumption of digital-to-analog converters (DACs) constitutes a\nsignificant proportion of the total power consumption in a massive multiuser\nmultiple-input multiple-output (MU-MIMO) base station (BS). Using 1-bit DACs\ncan significantly reduce the power consumption. This paper addresses the\nprecoding problem for the massive narrow-band MU-MIMO downlink system equipped\nwith 1-bit DACs at each BS. In such a system, the precoding problem plays a\ncentral role as the precoded symbols are affected by extra distortion\nintroduced by 1-bit DACs. In this paper, we develop a highly-efficient\nnonlinear precoding algorithm based on the alternative direction method\nframework. Unlike the classic algorithms, such as the semidefinite relaxation\n(SDR) and squared-infinity norm Douglas-Rachford splitting (SQUID) algorithms,\nwhich solve convex relaxed versions of the original precoding problem, the new\nalgorithm solves the original nonconvex problem directly. The new algorithm is\nguaranteed to globally converge under some mild conditions. A sufficient\ncondition for its convergence has been derived. Experimental results in various\nconditions demonstrated that, the new algorithm can achieve state-of-the-art\naccuracy comparable to the SDR algorithm, while being much more efficient (more\nthan 300 times faster than the SDR algorithm).\n