Mutual Information Analysis of Mixed-ADC MIMO Systems Over Rayleigh Channels Based on Random Matrix Theory

• Published in: IEEE transactions on wireless communications Vol. 19; no. 7; pp. 4894 - 4906
• Main Authors: Gao, Hang, Xiao, Kexin, Xia, Bin, Chen, Zhiyong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-07-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analog to digital conversion; Analog to digital converters; Antennas; Channels; Data analysis; Energy consumption; Energy conversion efficiency; energy efficiency; ergodic mutual information; Information management; Matrix theory; MIMO; MIMO (control systems); MIMO communication; mixed-ADC; Mutual information; Optimization; Quantization (signal); random matrix theory; Rayleigh channels; Receiving antennas; Scaling laws; Transmission efficiency; Wireless communication
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2020.2988250

The mixed analog-to-digital converters (ADC) architecture is a promising solution to the problem of high energy consumption of multiple-input multiple-output (MIMO) systems. In such a scheme, part of the received signals at the base station are quantized by high-resolution ADCs, while the others are quantized by one-bit ADCs. The signals quantized by the mixed-ADC architecture are correlated and non-identically distributed, which is different from the one-bit quantized MIMO systems. Moreover, unlike the previous works focusing on the achievable rate of mixed-ADC MIMO systems under linear detectors, we derive a closed-form expression of the ergodic mutual information between the transmit signals and the quantized outputs of the mixed-ADC architecture over Rayleigh channels, where the statistical property of the equivalent channel is characterized by random matrix theory. Then, we derive the power scaling law, which shows that reducing the transmit power will not sacrifice the transmission efficiency when the number of receive antennas increases. Furthermore, for any given number of antennas and user transmit power, the optimal number of one-bit ADCs for maximizing the energy efficiency is obtained. Moreover, constrained by a given hardware energy consumption, the theoretical mutual information shows obvious gains over the one of unquantized MIMO systems for low user transmit power.