Abstract
Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider outdoor scenarios, where a UAV and wireless devices are outdoor. In this paper, the problem of UAV placement is studied, where the goal is to find the optimum location of a single UAV that prolongs the lifetime of indoor wireless devices. First, a realistic Indoor-Outdoor path loss model is presented and the tradeoff introduced by this model is described. Then, the problem of UAV placement is formulated, where the goal is to find the optimum UAV location that prolongs the lifetime of indoor wireless devices. It can be proven that the constraint sets of the problem can be represented by a convex set in terms of three variables. To this end, an algorithm to find the optimum UAV location is proposed. Simulation results are presented to validate the effectiveness of the proposed algorithm.
Highlights
During disaster situations, Unmanned aerial vehicles (UAVs) can be deployed to provide continuous wireless coverage when the terrestrial network goes down [1]
The problem of UAV placement is formulated, where the goal is to find the optimum UAV location that prolongs the lifetime of indoor wireless devices
The constraint sets of the problem are proved that can be represented by a convex set in terms of three variables and an algorithm is proposed to find the optimum location of UAV
Summary
UAVs can be deployed to provide continuous wireless coverage when the terrestrial network goes down [1]. A few studies consider the indoor scenarios in which an outdoor UAV is used to provide wireless coverage for indoor wireless devices. Ter situations, where the placements of indoor wireless devices are symmetric across the dimensions of each floor, and apply the gradient descent algorithm to find an efficient placement of the UAV that minimizes the transmit power. In [4], the authors assume that the placements of indoor wireless devices are uniformly distributed in each floor and apply the particle swarm optimization algorithm to find an efficient location of a single UAV that minimizes the transmit power required to cover the indoor wireless devices. The authors of these research studies assume downlink scenarios from UAVs to indoor users
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