3 research outputs found
A Tractable Framework for Coverage Analysis of Cellular-Connected UAV Networks
Unmanned aerial vehicles (UAVs) have recently found abundant applications in
the public and civil domains. To ensure reliable control and navigation,
connecting UAVs to controllers via existing cellular network infrastructure,
i.e., ground base stations (GBSs), has been proposed as a promising solution.
Nevertheless, it is highly challenging to characterize the communication
performance of cellular-connected UAVs, due to their unique propagation
conditions. This paper proposes a tractable framework for the coverage analysis
of cellular-connected UAV networks, which consists of a new blockage model and
an effective approach to handle general fading channels. In particular, a
line-of-sight (LoS) ball model is proposed to capture the probabilistic
propagation in UAV communication systems, and a tractable expression is derived
for the Laplace transform of the aggregate interference with general Nakagami
fading. This framework leads to a tractable expression for the coverage
probability, which in turn helps to investigate the impact of the GBS density.
Specifically, a tight lower bound on the optimal density that maximizes the
coverage probability is derived. Numerical results show that the proposed LoS
ball model is accurate, and the optimal GBS density decreases when the UAV
altitude increases.Comment: 6 pages, 4 figures, submitted to the 2nd Workshop on "Integrating
UAVs into 5G and Beyond" in ICC 201
Air-to-Air Communications Beyond 5G: A Novel 3D CoMP Transmission Scheme
In this paper, a novel D cellular model consisting of aerial base stations
(aBSs) and aerial user equipments (aUEs) is proposed, by integrating the
coordinated multi-point (CoMP) transmission technique with the theory of
stochastic geometry. For this new D architecture, a tractable model for
aBSs' deployment based on the binomial-Delaunay tetrahedralization is
developed, which ensures seamless coverage for a given space. In addition, a
versatile and practical frequency allocation scheme is designed to eliminate
the inter-cell interference effectively. Based on this model, performance
metrics including the achievable data rate and coverage probability are derived
for two types of aUEs: {\it i)} the general aUE (i.e., an aUE having distinct
distances from its serving aBSs) and {\it ii)} the worst-case aUE (i.e., an aUE
having equal distances from its serving aBSs). Simulation and numerical results
demonstrate that the proposed approach emphatically outperforms the
conventional binomial-Voronoi tessellation without CoMP. Insightfully, it
provides a similar performance to the binomial-Voronoi tessellation which
utilizes the conventional CoMP scheme; yet, introducing a considerably reduced
computational complexity and backhaul/signaling overhead.Comment: 16 pages, 18 figures, Accepted by IEEE Transactions on Wireless
Communication
Millimeter-Wave Full-Duplex UAV Relay: Joint Positioning, Beamforming, and Power Control
In this paper, a full-duplex unmanned aerial vehicle (FD-UAV) relay is
employed to increase the communication capacity of millimeter-wave (mmWave)
networks. Large antenna arrays are equipped at the source node (SN),
destination node (DN), and FD-UAV relay to overcome the high path loss of
mmWave channels and to help mitigate the self-interference at the FD-UAV relay.
Specifically, we formulate a problem for maximization of the achievable rate
from the SN to the DN, where the UAV position, analog beamforming, and power
control are jointly optimized. Since the problem is highly non-convex and
involves high-dimensional, highly coupled variable vectors, we first obtain the
conditional optimal position of the FD-UAV relay for maximization of an
approximate upper bound on the achievable rate in closed form, under the
assumption of a line-of-sight (LoS) environment and ideal beamforming. Then,
the UAV is deployed to the position which is closest to the conditional optimal
position and yields LoS paths for both air-to-ground links. Subsequently, we
propose an alternating interference suppression (AIS) algorithm for the joint
design of the beamforming vectors and the power control variables. In each
iteration, the beamforming vectors are optimized for maximization of the
beamforming gains of the target signals and the successive reduction of the
interference, where the optimal power control variables are obtained in closed
form. Our simulation results confirm the superiority of the proposed
positioning, beamforming, and power control method compared to three benchmark
schemes. Furthermore, our results show that the proposed solution closely
approaches a performance upper bound for mmWave FD-UAV systems.Comment: This paper has been accepted by IEEE Journal on Selected Areas in
Communications, special issue on Multiple Antenna Technologies for Beyond 5