What is the Optimal Network Deployment for a Fixed Density of Antennas?

10/25/2017
by   Xuefeng Yao, et al.
0

In this paper, we answer a fundamental question: when the total number of antennas per square kilometer is fixed, what is the optimal network deployment? A denser network with a less number of antennas per base station (BS) or the opposite case. To evaluate network performance, we consider a practical network scenario with a fixed antennas density and multiuser multiple-input-multiple-output (MU-MIMO) operations for single-antenna users. The number of antennas in each BS is calculated by dividing the antenna density by the BS density. With the consideration of several practical network models, i.e., pilot contamination, a limited user equipment (UE) density and probabilistic line-of-sight (LoS)/non-line-of-sight (NLoS) path loss model, we evaluate the area spectral efficiency (ASE) performance. From our simulation results, we conclude that there exists an optimal BS density for a certain UE density to maximize the ASE performance when the antenna density is fixed. The intuition is that (i) by densifying the network with more BSs, we can achieve a receive power gain due to the smaller distance between the typical UE and its serving BS; (ii) by installing more antennas in each BS, we can achieve a beamforming gain for UEs using MU-MIMO, although such beamforming gain is degraded by pilot contamination; (iii) thus, a trade-off exists between the receive power gain and the beamforming gain, if we fix the antenna density in the network.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/10/2020

Area Spectral Efficiency and SINR Scaling Laws in Multi-Antenna Cellular Networks

We study the scaling laws of the signal-to-interference-plus-noise ratio...
research
09/10/2023

Trade-Off Between Beamforming and Macro-Diversity Gains in Distributed mMIMO

Industry and academia have been working towards the evolution from Centr...
research
12/29/2017

Network Deployment for Maximal Energy Efficiency in Uplink with Multislope Path Loss

This work aims to design the uplink (UL) of a cellular network for maxim...
research
11/08/2020

Learning to Beamform in Heterogeneous Massive MIMO Networks

It is well-known that the problem of finding the optimal beamformers in ...
research
01/25/2018

Timing Advance Estimation and Beamforming of Random Access Response in Crowded TDD Massive MIMO Systems

Timing advance (TA) estimation at the base station (BS) and reliable dec...
research
07/11/2019

Towards a Connected Sky: Performance of Beamforming with Down-tilted Antennas for Ground and UAV User Co-existence

Providing connectivity to aerial users such as cellular connected unmann...
research
01/14/2020

Scaling Laws of Dense Multi-Antenna Cellular Networks

We study the scaling laws of the signal-to-interference-plus-noise ratio...

Please sign up or login with your details

Forgot password? Click here to reset