Quantized Precoding for Massive MU-MIMO
By Sven Jacobsson, Giuseppe Durisi, Mikael Coldrey, Tom Goldstein, Christoph Studer. IEEE Transactions on Communications, 2016
328 citations recorded by the source corpus.
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 8 dB.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/46335b28e53934324050c0aa9182c609b6ffdf45
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
In Electrical and Electronic Engineering
Citations in the corpus
- An Overview of Signal Processing Techniques for Terahertz Communications (2020, background): “Since optimal precoding is exhaustive due to the cardinality of X̄tt in THz UMMIMO systems, only linear quantized precoders [228] are feasible, or perhaps very few optimized low-complexity nonlinear quantized precoders as well [229].”