A Joint Combiner and Bit Allocation Design for Massive MIMO Using Genetic Algorithm
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.
Cite
@article{arxiv.1711.06706,
title = {A Joint Combiner and Bit Allocation Design for Massive MIMO Using Genetic Algorithm},
author = {I. Zakir Ahmed and Hamid Sadjadpour and Shahram Yousefi},
journal= {arXiv preprint arXiv:1711.06706},
year = {2018}
}
Comments
Accepted for publication in Asilomar Conference on Signals, Systems, and Computers 2017