# Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications

## TL;DR

This paper introduces a resolution-adaptive hybrid MIMO architecture with novel ADC bit-allocation algorithms for mmWave receivers, enhancing spectral and energy efficiency by optimizing ADC resolution based on channel conditions.

## Contribution

It proposes new ADC bit-allocation algorithms, capacity approximation methods, and a worst-case ergodic rate analysis for hybrid MIMO systems with adaptive ADC resolution.

## Key findings

- BA algorithms outperform fixed-ADC in spectral efficiency
- Achieve 22% better energy efficiency with negligible quantization error
- Capacity and ergodic rate formulas validated by simulations

## Abstract

In this paper, we propose a hybrid analog-digital beamforming architecture with resolution-adaptive ADCs for millimeter wave (mmWave) receivers with large antenna arrays. We adopt array response vectors for the analog combiners and derive ADC bit-allocation (BA) solutions in closed form. The BA solutions reveal that the optimal number of ADC bits is logarithmically proportional to the RF chain's signal-to-noise ratio raised to the 1/3 power. Using the solutions, two proposed BA algorithms minimize the mean square quantization error of received analog signals under a total ADC power constraint. Contributions of this paper include 1) ADC bit-allocation algorithms to improve communication performance of a hybrid MIMO receiver, 2) approximation of the capacity with the BA algorithm as a function of channels, and 3) a worst-case analysis of the ergodic rate of the proposed MIMO receiver that quantifies system tradeoffs and serves as the lower bound. Simulation results demonstrate that the BA algorithms outperform a fixed-ADC approach in both spectral and energy efficiency, and validate the capacity and ergodic rate formula. For a power constraint equivalent to that of fixed 4-bit ADCs, the revised BA algorithm makes the quantization error negligible while achieving 22% better energy efficiency. Having negligible quantization error allows existing state-of-the-art digital beamformers to be readily applied to the proposed system.