dc.description.abstract | Unmanned Aerial Vehicles also known as drones have emerged as a promising technology to
provide seamless communication in a geographical area because of their high coverage, promising
rates, low cost, high mobility, adjustable height and flexible installation. Unmanned Aerial Vehicle
(UAV) base stations are mainly used and deployed when the capacity of the existing terrestrial
base stations is overly strained when data traffic shoots up. Due to the flexibility and mobility of
UAVs, it is convenient and effective to deploy UAVs as aerial base stations to provide wireless
services to ground users (GUs) during emergencies such as natural disasters and congestion. It is
difficult to deploy UAV base stations in space therefore optimization of their placement is
required. There are several deployment algorithm projects done for the deployment of UAV base
stations. However, most of them are mainly two-dimensional deploymentalgorithms and even the
few three-dimensional deployment algorithms focus majorly on optimizing the three-dimensional
placement of UAV base stations to maximize coverage, that is the area covered by the UAV base
stations ignoring capacity, that is the number of users the UAV base station can serve. In our
project, we proposed an efficient three-dimensional deployment algorithm of a UAV base station
in a heterogeneous network consisting of macro and Pico base stations during times when there is
a spike in data traffic. It majorly focuses on increasing capacity, that is maximizing the data rate
that is served to the users. Our system model assists the ground base stations using the UAV base
station to serve uniformly distributed users with maximum data rate taking into consideration the
impact of obstacle blockage over the wellknown air to ground (A2G) path model. In our work,
we proposed an efficient three dimensional deployment algorithm for a UAV base station in a
heterogeneous network. We optimized the three-dimensional placement of the UAV base station
to serve users with maximum data rate. We used coverage probability and throughput as
performance indicators to check the performance of our algorithm. | en_US |