Abstract-Massive multiuser (MU) multiple-input multipleoutput (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-toanalog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang's theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3-4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10 −3 , in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8 dB. Index Terms-Massive multi-user multiple-input multipleoutput, digital-to-analog converter, Bussgang's theorem, minimum mean-square error precoding, convex optimization, semidefinite relaxation, Douglas-Rachford splitting, sphere precoding.
Meanwhile, for 1-bit MU-MIMO, semidefinite relaxation (SDR) based precoding has been brought up in REF , where the SDR precoder is about 3dB worse compared with the ideal case for an uncoded BER of 10 −3 .
Quantized Precoding for Massive MU-MIMO
IEEE Transactions on Communications
IEEE Transactions on Communications
Mathematics Computer Science