A Joint Combiner and Bit Allocation Design for Massive MIMO Using Genetic Algorithm

TL;DR

This paper introduces a novel joint design of a combiner and variable-bit ADC allocation for massive MIMO systems, optimizing performance and power efficiency using a genetic algorithm.

Contribution

It derives a closed-form combiner expression considering quantization errors and proposes an optimal ADC bit allocation method with reduced complexity.

Findings

Unequal ADC resolution improves MIMO receiver performance.

The proposed genetic algorithm efficiently finds near-optimal ADC allocations.

Performance gains are achieved within power constraints.

Abstract

In this paper, we derive a closed-form expression for the combiner of a multiple-input-multiple-output (MIMO) receiver equipped with a minimum-mean-square-error (MMSE) estimator. We propose using variable-bit-resolution analog-to- digital converters (ADC) across radio frequency (RF) paths. The combiner designed is a function of the quantization errors across each RF path. Using very low bit resolution ADCs (1-2bits) is a popular approach with massive MIMO receiver architectures to mitigate large power demands. We show that for certain channel conditions, adopting unequal bit resolution ADCs (e.g., between 1 and 4 bits) on different RF chains, along with the proposed combiner, improves the performance of the MIMO receiver in the Mean Squared Error (MSE) sense. The variable-bit-resolution ADCs is still within the power constraint of using equal bit resolution ADCs on all paths (e.g., 2-bits). We propose a genetic algorithm in conjunction with the derived combiner to arrive at an optimal ADC bit allocation framework with significant reduction in computational complexity.