Mixed-ADC Massive MIMO

TL;DR

This paper proposes a mixed-ADC architecture for massive MIMO systems that uses a combination of one-bit and high-resolution ADCs to improve energy efficiency while maintaining high data rates, analyzed through information-theoretic tools.

Contribution

It introduces a novel mixed-ADC architecture for massive MIMO, providing analytical expressions for achievable rates and demonstrating energy efficiency gains over traditional systems.

Findings

Mixed-ADC architecture achieves near-capacity performance.

Dithering significantly improves system performance.

Energy consumption is reduced compared to conventional architectures.

Abstract

Motivated by the demand for energy-efficient communication solutions in the next generation cellular network, a mixed-ADC architecture for massive multiple input multiple output (MIMO) systems is proposed, which differs from previous works in that herein one-bit analog-to-digital converters (ADCs) partially replace the conventionally assumed high-resolution ADCs. The information-theoretic tool of generalized mutual information (GMI) is exploited to analyze the achievable data rates of the proposed system architecture and an array of analytical results of engineering interest are obtained. For fixed single input multiple output (SIMO) channels, a closed-form expression of the GMI is derived, based on which the linear combiner is optimized. The analysis is then extended to ergodic fading channels, for which tight lower and upper bounds of the GMI are obtained. Impacts of dithering and imperfect channel state information (CSI) are also investigated, and it is shown that dithering can remarkably improve the system performance while imperfect CSI only introduces a marginal rate loss. Finally, the analytical framework is applied to the multi-user access scenario. Numerical results demonstrate that the mixed-ADC architecture with a relatively small number of high-resolution ADCs is able to achieve a large fraction of the channel capacity of conventional architecture, while reduce the energy consumption considerably even compared with antenna selection, for both single-user and multi-user scenarios.