Optimizing Beams and Bits: A Novel Approach for Massive MIMO Base-Station Design

TL;DR

This paper introduces a novel joint optimization method for ADC bit resolution and analog beamforming in frequency-selective massive MIMO uplinks, employing submodular maximization to improve performance over existing approaches.

Contribution

It presents a new formulation of the joint optimization problem as constrained submodular set function maximization, enabling the design of an efficient approximation algorithm.

Findings

The proposed algorithm outperforms state-of-the-art methods.

The approach effectively handles practical constraints on beam and ADC resolution choices.

The method achieves significant improvements in weighted sum rate performance.

Abstract

We consider the problem of jointly optimizing ADC bit resolution and analog beamforming over a frequency-selective massive MIMO uplink. We build upon a popular model to incorporate the impact of low bit resolution ADCs, that hitherto has mostly been employed over flat-fading systems. We adopt weighted sum rate (WSR) as our objective and show that WSR maximization under finite buffer limits and important practical constraints on choices of beams and ADC bit resolutions can equivalently be posed as constrained submodular set function maximization. This enables us to design a constant-factor approximation algorithm. Upon incorporating further enhancements we obtain an efficient algorithm that significantly outperforms state-of-the-art ones.