Performance Analysis for Practical Unmanned
Aerial Vehicle Networks with LoS/NLoS
Transmissions
Chang Liu
, Ming Ding
†
, Chuan Ma
, Qingzhi Li
, Zihuai Lin
and Ying-Chang Liang
‡
School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia
†
Data61, CSIRO, Australia
‡
University of Electronic Science and Technology of China (UESTC), Chengdu, China
Email: {cliu6845, qili3928}@uni.sydney.edu.au, {chuan.ma, zihuai.lin}@sydney.edu.au, Ming.Ding@data61.csicro.au, liangyc@ieee.org
Abstract—In this paper, we provide a performance analysis for
practical unmanned aerial vehicle (UAV)-enabled networks. By
considering both line-of-sight (LoS) and non-line-of-sight (NLoS)
transmissions between aerial base stations (BSs) and ground
users, the coverage probability and the area spectral efficiency
(ASE) are derived. Considering that there is no consensus on the
path loss model for studying UAVs in the literature, in this paper,
three path loss models, i.e., high-altitude model, low-altitude
model and ultra-low-altitude model, are investigated and com-
pared. Moreover, the lower bound of the network performance is
obtained assuming that UAVs are hovering randomly according
to homogeneous Poisson point process (HPPP), while the upper
bound is derived assuming that UAVs can instantaneously move to
the positions directly overhead ground users. From our analytical
and simulation results for a practical UAV height of 50 meters,
we find that the network performance of the high-altitude model
and the low-altitude model exhibit similar trends, while that of
the ultra-low-altitude model deviates significantly from the above
two models. In addition, the optimal density of UAVs to maximize
the coverage probability performance has also been investigated.
I. INTRODUCTION
Due to the flying nature of unmanned aerial vehicles
(UAVs), base stations (BSs) can be mounted on the UAV
to support wireless communications and improve the perfor-
mance of cellular networks. For example, UAV-mounted base
stations (UAV-BSs) are introduced when a natural disaster
interrupts communications or ground base stations are over-
loaded [1]. Compared with ground BSs, the flexibility of UAV-
BSs allows them to adapt their locations to the demand of
users.
Most of the literature on the UAV-BS focuses on its de-
ployment. The work in [2] proposed that fixed-wing UAVs
at a constant height are more applicable for aerial networks
due to less power consumption. Positions of UAV-BSs were
modeled as a 3D Poisson Point Process (3D-PPP) distribution
with a limited height in [1], but the analysis in [3] showed that
the flexible height of UAV is not as helpful as a well-chosen
fixed altitude. In [4], UAV-mounted mobile base stations were
The work of Y.-C. Liang is funded by National Natural Science Foundation
of China under Grants 61571100, 61631005 and 61628103.
deployed in a fixed altitude and placed along an optimal
trajectory to cover as much as user equipment (UE) whose
locations are already known in a given area.
Beyond the UAV deployment, the performance of 3D net-
works also attracts much attention in the existing literature.
The work in [3] analyzed the average downlink spectral
efficiency without considering the environment noise, while
the authors of [5] evaluated the performance of UAV at a low
altitude platform in terms of the coverage area and transmit
power. Similarly, the optimal deployment model in [6] led to
the analysis of coverage and transmit power. Furthermore, the
analysis in [7] introduced a tractable analytical framework for
the coverage and the rate in UAV based network with the
coexistence of device-to-device (D2D) network.
Although the path loss model has been considered as a
key factor in the performance analysis for UAV networks,
there is no consensus on this issue yet. For example, the
work in [1] and [4] only considered the UAV hovering in a
LoS dominated network for simplicity. To conduct a practical
analysis for UAV, the authors of [8] proposed a general path
loss model which considers both LoS and NLoS connections
and their occurrence probabilities, depending on the elevation
angle between a UAV and a user. Despite that this model
has been widely adopted as the high-altitude model (a typical
height is around 1000 meters), the network performance has
not been investigated due to the complexity of the proposed
model. On the other hand, the work in [9] provided a network
analysis of the terrestrial cellular network where the antenna
height between BSs and users is around 10m∼30m, together
with 3GPP LoS and NLoS models. Considering that the height
of UAVs is comparable with that of ground base stations
in future UAV networks, the curent macrocell-to-UE model
(a typical height is around 32 meters) and picocell-to-UE
model (a typical height is around 10 meters) proposed for
terrestrial communication in 3GPP standard can also be ap-
plied to the UAV-based network. Such macrocell-to-UE model
and picocell-to-UE model are referred to as the low-altitude
model and the ultra-low-altitude model hereafter. To our best
knowledge, the path loss model for UAV-BSs has not been
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