Digital and Hybrid Precoding Designs in Massive MIMO with Low-Resolution ADCs
Mengyuan Ma, Nhan Thanh Nguyen, Italo Atzeni, A. Lee Swindlehurst, and, Markku Juntti

TL;DR
This paper develops and optimizes precoding strategies for massive MIMO systems with low-resolution ADCs, demonstrating significant spectral efficiency improvements especially with partially connected hybrid architectures.
Contribution
It introduces a novel precoding design framework for digital, fully connected, and partially connected hybrid beamforming architectures with low-resolution ADCs, using a tight SE lower bound and majorization-minorization optimization.
Findings
Partially connected hybrid precoding achieves near digital SE in 1-bit systems.
Proposed designs outperform existing methods in low-resolution ADC scenarios.
PC hybrid beamforming offers a cost-effective alternative with high spectral efficiency.
Abstract
Low-resolution analog-to-digital converters (ADCs) have emerged as an efficient solution for massive multiple-input multiple-output (MIMO) systems to reap high data rates with reasonable power consumption and hardware complexity. In this paper, we study precoding designs for digital, fully connected (FC) hybrid, and partially connected (PC) hybrid beamforming architectures in massive MIMO systems with low-resolution ADCs at the receiver. We aim to maximize the spectral efficiency (SE) subject to a transmit power budget and hardware constraints on the analog components. The resulting problems are nonconvex and the quantization distortion introduces additional challenges. To address them, we first derive a tight lower bound for the SE, based on which we optimize the precoders for the three beamforming architectures under the majorization-minorization framework. Numerical results validate…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Radio Frequency Integrated Circuit Design · Advanced Wireless Communication Techniques
