Page 413 - Kaleidoscope Academic Conference Proceedings 2024

Energy efficient UAV positioning for throughput

optimization *

Pimmy Gandotra Varun Gupta Brejesh Lall Abdelaali Chaoub
JIIT/BSTTM, IITD BSTTM Department of EE Department of Telecom
Noida/Delhi IIT Delhi IIT Delhi INPT
New Delhi, India New Delhi New Delhi, India Rabat, Morocco
pimmy.gandotra@gmail.com varun.g1997@gmail.com brejesh@ee.iitd.ac.in chaoub.abdelaali@gmail.com

Abstract—In the digital era where network connectivity has and 3D trajectory planning issues, along with power and
emerged as indispensable for the users, non-terrestrial networks flight duration limits, QoS requirements, cost constraints
(NTNs) have gained significant traction. The NTN technology and design considerations are still impeding the widespread
provides coverage to areas where base stations find difficulty
in reaching. Using drones/unmanned aerial vehicles (UAVs) has adoption of UAV-aided cellular connections and thus calling
introduced the notion of flying BSs. In this paper, an efficient for further research.
placement of UAVs is proposed, with focus on energy efficiency.
The proposed scheme focuses on maximizing coverage with The UAVs’ capability to establish excellent line of sight (LoS)
throughput maximization and latency reduction, while optimizing connectivity [2] allows them to reduce signal blocking and
the UAV height (or vertical positioning) and energy. The opti-
mization function is formulated to optimize the latency as well as shadowing. They can travel towards ground users everywhere
the power levels, as a linear combination of weights. The results and maintain reliable air-ground connections with minimal
depict the efficacy of the proposed scheme. transmit power because of their flexible height and mobility.
Index Terms—UAV, NTN, HAPS, 5G, Beyond 5G Despite the aforementioned strengths of the UAV technology
as a strong enabler of broadband connectivity in remote
I. INTRODUCTION
and rural locations, the limited on-board power is still a
To meet the surging demands for massive connectivity, serious bottleneck that needs to be tackled before realistic
enhanced coverage and cost efficiency, non-terrestrial deployments. Hence, the energy efficiency is at the core of
networks (NTNs) [1] have emerged as an effective solution the UAV-assisted remote wireless connectivity.
for complementing the terrestrial infrastructure and ensuring
A. State of the Art
service provisioning in uncovered or under-served areas.
Among the NTNs, UAV- and high altitude platform station Many state-of-the-art researches have focused on energy
(HAPS)-enabled networks [2] [3] are expected to be vital optimization by means of optimizing either the trajectory of
components for the future 5G wireless communication the UAV in case of mobile drones, or its position by finding
networks (WCNs) and beyond, to deliver broadband the optimal 3D coordinates that give the maximum coverage
connectivity to infrastructure-deficient areas [4]. with the minimum power requirements. The 3D positioning
has been investigated in [5], wherein the UAV is acting as
HAPSs are rapidly deployable in adverse conditions (e.g. the BS. The work has not only focused on optimizing the
disasters and early warning systems) and usually at a fixed coverage area but also the flying time of the UAV. Further, the
height above the ground. They can fly at high altitudes (over swarm size minimization problem has also been discussed,
10 kilometres), have long flight periods, are quasi-stationary, provided that a given coverage constraint is met. In [6], the
cover a large area and have a big payload capacity. However, UAV’s placement in the 3D space and the resource allocation
these are expensive and complex to build and deploy. UAVs for the FDMA scheme are jointly optimized, such that the
or the low amplitude platforms (LAP), on the other hand, throughput is maximized. The authors have used an iterative
are compact, cost-effective, scalable and rapidly deployable. algorithm to solve the problem by optimizing the throughput
They can hover at low altitudes (below 10 kilometres) and with respect to one parameter at a time. In [7], authors
are able to fly swiftly and smoothly. On the downside, UAVs have formulated a nonlinear optimization problem which
have short flight periods due to their limited battery lifetime. determines the optimal 3D position of the UAV as well as its
They can be used as airborne access points (e.g. base stations coverage area, such that the number of users covered by the
(BSs)) to provide on-demand connectivity, traffic offloading UAV (e.g. the UAV capacity) is maximized. Similarly, the
and high data rate wireless access in hotspots and remote UAV’s location is adjusted, in [8], based on the distribution
locations as well as during temporary events such as sports patterns of the users on the ground.
and festivals. This, however, comes at the expense of some
key challenges. For instance, optimal UAV BS positioning Besides power optimization, several efforts have been

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