VLSI Design of a Nonparametric Equalizer for Massive MU-MIMO

TL;DR

This paper introduces a novel VLSI design for a nonparametric equalizer in massive MU-MIMO systems that matches the performance of traditional methods without needing signal or noise power knowledge, reducing complexity.

Contribution

The paper presents the first VLSI implementation of a parameter-free equalizer that achieves near-optimal performance without prior knowledge of system parameters.

Findings

NOPE matches L-MMSE performance in massive MU-MIMO.

The design is resilient to hardware impairments.

Synthesis in 28nm CMOS demonstrates practical feasibility.

Abstract

Linear minimum mean-square error (L-MMSE) equalization is among the most popular methods for data detection in massive multi-user multiple-input multiple-output (MU-MIMO) wireless systems. While L-MMSE equalization enables near-optimal spectral efficiency, accurate knowledge of the signal and noise powers is necessary. Furthermore, corresponding VLSI designs must solve linear systems of equations, which requires high arithmetic precision, exhibits stringent data dependencies, and results in high circuit complexity. This paper proposes the first VLSI design of the NOnParametric Equalizer (NOPE), which avoids knowledge of the transmit signal and noise powers, provably delivers the performance of L-MMSE equalization for massive MU-MIMO systems, and is resilient to numerous system and hardware impairments due to its parameter-free nature. Moreover, NOPE avoids computation of a matrix inverse and only requires hardware-friendly matrix-vector multiplications. To showcase the practical advantages of NOPE, we propose a parallel VLSI architecture and provide synthesis results in 28nm CMOS. We demonstrate that NOPE performs on par with existing data detectors for massive MU-MIMO that require accurate knowledge of the signal and noise powers.