Finite-Alphabet MMSE Equalization for All-Digital Massive MU-MIMO mmWave Communication
Journal article, 2020

We propose finite-alphabet equalization, a new paradigm that restricts the entries of the spatial equalization matrix to low-resolution numbers, enabling high-throughput, low-power, and low-cost hardware equalizers. To minimize the performance loss of this paradigm, we introduce FAME, short for finite-alphabet minimum mean- square error (MMSE) equalization, which is able to significantly outperform a naive quantization of the linear MMSE matrix. We develop efficient algorithms to approximately solve the NP-hard FAME problem and showcase that near-optimal performance can be achieved with equalization coefficients quantized to only 1-3 bits for massive multi-user multiple-input multiple-output (MU-MIMO) millimeter-wave (mmWave) systems. We provide very-large scale integration (VLSI) results that demonstrate a reduction in equalization power and area by at least a factor of 3.9x and 5.8x, respectively.

hardware implementation

massive multi-user MIMO

minimum mean-square error (MMSE)

Millimeter wave (mmWave)

spatial equalization

quantization

Author

Oscar Castaneda

Cornell University

Cornell Tech

Sven Jacobsson

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Giuseppe Durisi

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Tom Goldstein

University of Maryland

Christoph Studer

Cornell Tech

Cornell University

IEEE Journal on Selected Areas in Communications

0733-8716 (ISSN)

Vol. 38 9 2128-2141

Subject Categories

Telecommunications

Computational Mathematics

Signal Processing

DOI

10.1109/JSAC.2020.3000840

More information

Latest update

10/7/2020