Downlink Spectral Efficiency of Massive MIMO Systems with Mutual Coupling

Abstract

Massive multiple-input multiple-output (MIMO) is a profitable technique to greatly boost spectral efficiency, which has been embraced by the fifth-generation (5G) and sixth-generation (6G) mobile communication systems. By exploiting appropriate downlink precoding algorithms, base stations (BSs) equipped with a large number of antennas are able to provide service to multiple users as well as several cells at the same time and frequency. However, the mutual coupling effect due to the compact antenna array gives misleading results in massive MIMO communication systems. In this paper, we focus on the mutual coupling effect for massive MIMO systems with maximal ratio transmission (MRT), zero-forcing (ZF), regularize ZF (RZF), and minimum mean square error (MMSE) precoding to solve the mutual coupling problem. Additionally, we construct the closed-form expressions of the spectral efficiency (SE) to evaluate the effect of mutual coupling on system performance. Simulation results validate the effectiveness of the proposed mutual coupling effect assessment method and demonstrate the significant impacts of mutual coupling on massive MIMO system performance.

Advancements and Challenges in Scalable Modular Antenna Arrays for 5G Massive MIMO Networks

“…Due to the large number of antennas, the SINR can be substantially improved, thus increasing the spectral efficiency. Empirical studies, such as those presented at various IEEE conferences, provide real-world validation of these theoretical models, showing how Massive MIMO can exploit the available spectrum more effectively than ever before [33].…”

MIMO System Capacity based on Multiple fading channels and varying numbers of antennas including the comparison of MIMO-NOMA and MIMO-OMA

“…This means that the energy of the wireless transmission can create the electromagnetic waves superimposed at the mobile station (MS) terminal, so strengthening the signal received. There has been a lot of work on mMIMO which has been shown in various works [5][6][7][8][9]. But the expense of mMIMO's implementation cost is still too expensive, which is mostly seen in the price of Radio Frequency (RF) modules and auxiliaries the expensive price of the significant channel estimate overhead, the cost of deploying dense stations, as well as the lengthy estimating process.…”