Massive MIMO Systems for 5G and beyond Networks—Overview, Recent Trends, Challenges, and Future Research Direction

Abstract

The global bandwidth shortage in the wireless communication sector has motivated the study and exploration of wireless access technology known as massive Multiple-Input Multiple-Output (MIMO). Massive MIMO is one of the key enabling technology for next-generation networks, which groups together antennas at both transmitter and the receiver to provide high spectral and energy efficiency using relatively simple processing. Obtaining a better understating of the massive MIMO system to overcome the fundamental issues of this technology is vital for the successful deployment of 5G—and beyond—networks to realize various applications of the intelligent sensing system. In this paper, we present a comprehensive overview of the key enabling technologies required for 5G and 6G networks, highlighting the massive MIMO systems. We discuss all the fundamental challenges related to pilot contamination, channel estimation, precoding, user scheduling, energy efficiency, and signal detection in a massive MIMO system and discuss some state-of-the-art mitigation techniques. We outline recent trends such as terahertz communication, ultra massive MIMO (UM-MIMO), visible light communication (VLC), machine learning, and deep learning for massive MIMO systems. Additionally, we discuss crucial open research issues that direct future research in massive MIMO systems for 5G and beyond networks.

Scaling Laws of Scheduling Gain for Uplink Massive MIMO Systems: Is User Scheduling Still Beneficial for Massive MIMO?

“…As explained in Section 4, we consider two scenarios for CSI availability for user scheduling at the BS, namely non-ideal CSI and near-ideal CSI. The exhaustive search for the optimal user selection algorithm uses the exact SINR formula in (4) as the selection metric; thus, the CSI availability for user scheduling only affects the scheduling gain for the optimal user selection algorithm. Conversely, SUS and SIRUS are not influenced by the CSI availability for user scheduling because the user selection metrics are calculated using the estimated channel.…”

“…Massive multiple input-multiple output (MIMO), in which the base station (BS) is equipped with a few hundreds of antenna arrays, is a key feature for 5G NR, used to satisfy the target data rate requirement [4]. With the emerging large number of antennas, many users can be served simultaneously using given time and frequency resources through multiuser MIMO [5], which can significantly improve the spectral efficiency [6].…”

“…To further improve the achievable sum rate in massive MIMO systems, a proper user scheduling algorithm is typically employed in wireless communication systems [4], which selects the number of users to be served simultaneously in a spatial multiplexing manner. Therefore, many studies have recently been conducted to investigate the user scheduling algorithm for various massive MIMO systems [12].…”

“…τ 2 and c ∆ = K − 1 for simplicity. Then, the first-order derivative of (24) can be written as ∂κ ip 2,MF ∂M = (log 2 e) 2 a 2 c K − 2 2a − a 2 M 2 + 2cM + c 2(aM + c)4 .…”

Backhaul-Aware Dimensioning and Planning of Millimeter-Wave Small Cell Networks

“…Thus, a line-of-sight (LOS) communication path with highly directional beams and high-gain antennas is required to achieve several gigabits per second [10]. Thanks to the recent advancement in hardware design, this can be realized with massive MIMO implementations using a large number of very low power antennas [11,12]. MIMO beamforming has the benefit of reduced inter-antenna interference due to the high directivity of the individual links.…”