1,102 research outputs found
Backhaul-aware Robust 3D Drone Placement in 5G+ Wireless Networks
Using drones as flying base stations is a promising approach to enhance the
network coverage and area capacity by moving supply towards demand when
required. However deployment of such base stations can face some restrictions
that need to be considered. One of the limitations in drone base stations
(drone-BSs) deployment is the availability of reliable wireless backhaul link.
This paper investigates how different types of wireless backhaul offering
various data rates would affect the number of served users. Two approaches,
namely, network-centric and user-centric, are introduced and the optimal 3D
backhaul-aware placement of a drone-BS is found for each approach. To this end,
the total number of served users and sum-rates are maximized in the
network-centric and user-centric frameworks, respectively. Moreover, as it is
preferred to decrease drone-BS movements to save more on battery and increase
flight time and to reduce the channel variations, the robustness of the network
is examined as how sensitive it is with respect to the users displacements.Comment: in Proc. IEEE ICC2017 Workshops, FlexNets201
3D Placement of an Unmanned Aerial Vehicle Base Station (UAV-BS) for Energy-Efficient Maximal Coverage
Unmanned Aerial Vehicle mounted base stations (UAV-BSs) can provide wireless
services in a variety of scenarios. In this letter, we propose an optimal
placement algorithm for UAV-BSs that maximizes the number of covered users
using the minimum transmit power. We decouple the UAV-BS deployment problem in
the vertical and horizontal dimensions without any loss of optimality.
Furthermore, we model the UAV-BS deployment in the horizontal dimension as a
circle placement problem and a smallest enclosing circle problem. Simulations
are conducted to evaluate the performance of the proposed method for different
spatial distributions of the users
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