Energy Efficiency Optimization for Millimeter Wave System with Resolution-Adaptive ADCs

TL;DR

This paper proposes an energy-efficient optimization framework for uplink millimeter wave MIMO systems with adaptive ADCs, jointly optimizing beamforming and ADC bit allocation to enhance system performance.

Contribution

It introduces a novel joint optimization method for beamspace hybrid combining and ADC bit allocation using fractional programming and iterative algorithms for mmWave systems.

Findings

Significant energy efficiency gains over baseline methods

Effective joint optimization of beamforming and ADC resolution

Demonstrated practical benefits through simulations

Abstract

This letter investigates the uplink of a multi-user millimeter wave (mmWave) system, where the base station (BS) is equipped with a massive multiple-input multiple-output (MIMO) array and resolution-adaptive analog-to-digital converters (RADCs). Although employing massive MIMO at the BS can significantly improve the spectral efficiency, it also leads to high hardware complexity and huge power consumption. To overcome these challenges, we seek to jointly optimize the beamspace hybrid combiner and the ADC quantization bits allocation to maximize the system energy efficiency (EE) under some practical constraints. The formulated problem is non-convex due to the non-linear fractional objective function and the non-convex feasible set which is generally intractable. In order to handle these difficulties, we first apply some fractional programming (FP) techniques and introduce auxiliary variables to recast this problem into an equivalent form amenable to optimization. Then, we propose an efficient double-loop iterative algorithm based on the penalty dual decomposition (PDD) and the majorization-minimization (MM) methods to find local stationary solutions. Simulation results reveal significant gain over the baselines.