Coordinated Multicell Beamforming and Power Allocation for Massive MIMO with Low-Resolution ADC/DAC

TL;DR

This paper proposes a novel coordinated beamforming and power allocation method for massive MIMO systems with low-resolution ADC/DAC, demonstrating power minimization and SINR guarantees through UL-DL duality and iterative algorithms.

Contribution

It introduces a new UL-DL duality framework for coarsely quantized massive MIMO and develops an iterative algorithm for optimal power and beamforming design.

Findings

Strong UL-DL duality holds even with low-resolution converters.

The proposed algorithm achieves near-optimal power minimization.

Simulation confirms effectiveness in reducing power consumption.

Abstract

In this work, we present a solution for coordinated beamforming and power allocation when base stations employ a massive number of antennas equipped with low-resolution analog-to-digital and digital-to-analog converters. We address total power minimization problems of the coarsely quantized uplink (UL) and downlink (DL) communication systems with target signal-to-interference-plus-noise ratio (SINR) constraints. By combining the UL problem with minimum mean square error combiners and deriving the Lagrangian dual of the DL problem, we prove UL-DL duality and show there is no duality gap even with coarse data converters. Inspired by strong duality, we devise an iterative algorithm to determine the optimal UL transmit powers, and then linearly amplify the UL combiners with proper weights to acquire the optimal DL precoder. Simulation results validate strong duality and evaluate the proposed method in terms of total power consumption and achieved SINR.