ADC Bit Allocation under a Power Constraint for MmWave Massive MIMO Communication Receivers

TL;DR

This paper introduces a low-complexity bit allocation method for mmWave massive MIMO systems that optimizes ADC resolution under power constraints, improving communication performance over traditional low-resolution ADCs.

Contribution

It proposes a near-optimal, low-complexity bit allocation algorithm for ADCs in mmWave massive MIMO systems that minimizes quantization error under power limits.

Findings

Better communication performance than conventional low-resolution ADCs.

Achieves similar or lower power consumption with improved accuracy.

Effective exploitation of channel sparsity in beamspace.

Abstract

Millimeter wave (mmWave) systems operating over a wide bandwidth and using a large number of antennas impose a heavy burden on power consumption. In a massive multiple-input multiple-output (MIMO) uplink, analog-to-digital con- verters (ADCs) would be the primary consumer of power in the base station receiver. This paper proposes a bit allocation (BA) method for mmWave multi-user (MU) massive MIMO systems under a power constraint. We apply ADCs to the outputs of an analog phased array for beamspace projection to exploit mmWave channel sparsity. We relax a mean square quantization error (MSQE) minimization problem and map the closed-form solution to non-negative integer bits at each ADC. In link-level simulations, the proposed method gives better communication performance than conventional low-resolution ADCs for the same or less power. Our contribution is a near optimal low-complexity BA method that minimizes total MSQE under a power constraint.