Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Abstract

Abstract:Massive MIMO technique offers significant performance gains for the future of wireless communications via improving the spectral efficiency, energy efficiency and the channel quality with simple linear processing such as maximum-ratio transmission (MRT) or zero-forcing (ZF) by providing each user a large degree of freedom. In this paper, the system performance gains are studied in a multi-cell downlink massive MIMO system under the main considerations such as perfect channel estimation, imperfect channel estimation and the effect of interference among cells due to pilot sequences contamination. Then, mathematical expressions are derived for these gains i.e., spatial multiplexing gain, array gain and spatial diversity gain. After that, essential tradeoffs among these gains are considered under the effect of non-orthogonal interference, these tradeoffs are: spatial diversity gain vs. spatial multiplexing gain and array gain vs. spatial multiplexing gain. Simulation results show that the unbounded number of base station antennas boosts the array gain through concentrating the energy to spatial directions where users are sited, hence diminishing loss in array gain due to pilot contamination. The simulation results reveal also that massive MIMO strengthens the spatial multiplexing gain through increasing the number of served users via the same system resources in spite the effect of inter-cell interference. Finally, the spatial diversity gain is measured in term of outage probability and the simulation results show that raising the number of antennas will improve the outage probability. Meanwhile increasing the number of served users will lead to degrade the outage probability per user due to non-orthogonal interference from other cells.

Worst Cell Based Pilot Allocation in Massive MIMO Systems

“…Massive multiple-input multiple-output (MIMO) techniques have been broadly investigated over the last two decades to keep up with the exponential increases in mobile data traffic in future 5G wireless systems [1][2][3][4][5][6], whereby a base station (BS) endowed with a very huge number of antennas serving many users concurrently. Massive MIMO has been considered as one of the main techniques which provide reliable and green communication [7,8], especially in smart cities networks.…”

“…Reusing orthogonal pilot sequences results in a problem called pilot contamination (PC). PC causes major limitations in the performance of massive MIMO systems, even though the number of BS antennas goes to infinity, and thus PC has become one of the main research topics in massive MIMO systems [4,5]. A lot of efforts have been made to overcome this challenging issue of PC [10][11][12][13][14][15][16][17][18][19].…”

Beam Grouping Based RS Resource Reuse and De-Contamination in Large Scale MIMO Systems

“…They are already considered to be incorporated into the 3rd generation partnership project (3GPP) standard body, and are referred to as Full-Dimension MIMO (FD-MIMO) systems [1][2][3][4][5]. However, most of the performance analysis for LS-MIMO systems disregard its high implementation complexity and the overhead required for reference signals (RSs).…”

Design of an Energy Efficient Future Base Station with Large-Scale Antenna System

“…Due to the limited spectrum resources, it is also inevitable for the number of transmitter (TX) antennas in the BS to continuously increase [11]. Thus, we assume that a future BS has a large number of TX antennas, that is a large-scale (LS) antenna system or LS multiple-input multiple-output (MIMO) [16][17][18]. Actually, in the case of a BS with LS-MIMO, the resource allocation problems are easier to solve if the channel properties provided by LS-MIMO systems are exploited smartly [19,20].…”