Optimal Low‐Power Design of a Multicell Multiuser Massive MIMO System at 3.7 GHz for 5G Wireless Networks

Abstract

Massive MIMO techniques are expected to deliver significant performance gains for the future wireless communication networks by improving the spectral and the energy efficiencies. In this paper, we propose a method to optimize the positions, the coverage, and the energy consumption of the massive MIMO base stations within a suburban area in Ghent, Belgium, while meeting the low power requirements. The results reveal that massive MIMO provides better performances for the crowded scenario where users’ mobility is limited. With 256 antennas, a massive MIMO base station can simultaneously multiplex 18 users at the same time-frequency resource while consuming 8 times less power and providing 200 times more capacity than a 4G reference network for the same coverage. Moreover, a pilot reuse pattern of 3 is recommended in a multiuser multicell environment to obtain a good tradeoff between the high spectral efficiency and the low power requirement.

Multi-Objective Optimization of Massive MIMO 5G Wireless Networks towards Power Consumption, Uplink and Downlink Exposure

“…A multi-cell massive MIMO network system consisting of L cells, each containing one BS with multiple antenna elements is considered in this study, as shown in Figure 1. This model is similar to the ones proposed in [18][19][20] in which each BS communicates coherently with the single-antenna users using the time division duplex (TDD) operating mode. This latter is considered to obtain the downlink signaling informations from the uplink pilots thanks to the channel reciprocity property it relies on.…”

“…In this paper, we proceed with the simulations of the optimal massive MIMO 5G networks to investigate the scenarios described above. We apply a capacity-based network deployment tool proposed in [19], in which the optimization algorithm in Figure 3 is implemented. The optimization algorithm of the tool is based on the BS-user association principle and optimizes the initial set of the base stations deployed in the area of interest while meeting the following optimization constraints: (i) the obtained network must have the least possible power consumption, (ii) the DL and UL EMF exposure resulting from the obtained 5G networks must be minimal, (iii) the network must respond to the instantaneous bit rates (voice and data) requested by the users and (iv) must provide a coverage for at least 95% of the users.…”

“…To ensure the massive MIMO requirements in terms of higher data rates imposed by the 5G applications are met, we consider the 3GPP LTE Rel. 8 path loss model PL(d) (Equation 24) and the power consumption model proposed in [19,34].…”

“…Moreover, the user equipments (UE) are assumed to have one single transmit antenna. The moderate inter-cell interference resulting from the pilot contamination effects is modeled by the use of the pilot reuse factor F = 3 [19]. For each considered scenario, we run multiple simulations (40) to ensure we obtain a statistically relevant estimation of the parameters investigated (e.g., the number of BSs, the power consumption and the DL and UL EMF exposure) [32].…”

Mitigating the Interference Caused by Pilot Contamination in Multi-cell Massive Multiple Input Multiple Output Systems Using Low Density Parity Check Codes in Uplink Scenario

“…Liu et al [14] have proposed a graph coloring based pilot assignment scheme by utilizing the large-scale coefficients between the access points and user terminals which is capable of reducing the effect of pilot contamination. A method for optimization of coverage, positions, and energy consumption of m-MIMO for low power requirements has been proposed [15]. Al-hubaishi et al [16] have proposed a partial pilot allocation scheme capable of increasing the uplink rate of users in a multi-cell scenario by exploiting the large-scale characteristics of fading channel so that users having poor channel conditions are saved from harsh interference.…”