Massive MIMO Systems with Low-Resolution ADCs: Achievable Rates and Allocation of Quantization Bits. (17th February 2023)

• Record Type: Journal Article
• Authors: Zhang, Wence; Xia, Jing; Bao, Xu
• Other Names: Morosi Simone Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2023(2023)
• Publication Date: 2023-02-17
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2023/4012841
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : In massive multiple-input multiple-output (MIMO) systems, the large number of high-resolution analog-to-digital converters (ADCs) lead to high hardware cost and power consumption. In this work, the uplink achievable rates of massive MIMO systems with low-resolution ADCs are studied with consideration of both "Uniform-ADC" that uses ADCs with the same number of quantization bits and "Mixed-ADC" that allows the use of ADCs with different resolutions. By leveraging an additive quantization noise model (AQNM), the asymptotic achievable rates are obtained for maximum ratio combining (MRC), zero-forcing (ZF), and linear minimum mean squared error (LMMSE) receivers in very simple forms. Taking advantages of the theoretical results, we propose two criteria for allocation of quantization bits. It is found that the optimal quantization bits allocation for LMMSE is Mixed-ADCs with number of quantization bits that are polarized, while Uniform-ADC is optimal for MRC and ZF. When there is a constraint on the total ADC power consumption, the proposed quantization-bit allocation scheme for LMMSE becomes Uniform-ADC when the transmit signal-to-noise ratio (SNR) is below a threshold, which is related to the system scale and the ADC power consumption. The theoretical results are verified by Monte-Carlo simulations.