Quantized Precoding for Massive MU-MIMO
Journal article, 2017

Massive multiuser (MU) multiple-input multiple-output (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-to-analog 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 8dB.


Sven Jacobsson

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Giuseppe Durisi

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Mikael Coldrey


Tom Goldstein

University of Maryland

Christoph Studer

Cornell University

IEEE Transactions on Communications

0090-6778 (ISSN)

Vol. 65 11 4670-4684 7967843

Massive MIMO systems with low-resolution converters

Swedish Foundation for Strategic Research (SSF) (ID14-0022), 2015-03-01 -- 2020-02-28.


C3SE (Chalmers Centre for Computational Science and Engineering)

Subject Categories

Communication Systems



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