### Full-duplex UAV relay positioning for vehicular networks

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Author: Pourbaba, Pouya1
Organizations: 1University of Oulu, Faculty of Information Technology and Electrical Engineering, Communications Engineering
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 5.5 MB)
Pages: 46
Language: English
Published: Oulu : P. Pourbaba, 2019
Publish Date: 2019-05-20
Thesis type: Master's thesis (tech)
Tutor: Rajatheva, Rajatheva
Reviewer: Rajatheva, Rajatheva
Description:

Abstract

The unmanned aerial vehicles (UAVs) can be deployed as aerial base stations or wireless relays to enhance the coverage and guarantee the quality of service (QoS) of wireless networks. In this thesis, the positioning of a full-duplex (FD) UAV as a relay to provide coverage for an FD vehicular network is investigated. This problem is solved using two different methods. In both of the methods, the problem is formulated using a predefined set of locations for the UAV. Then this problem is solved for different configurations of the ground users and an optimal location is selected for the UAV to operate at.

In the first approach, given the position of the vehicular users on the ground, a novel algorithm is proposed to find a location for the UAV to satisfy the QoS requirements of the vehicles in the network. The positioning problem is formulated as an $$\mathcal{l}_0$$ minimization which is non-combinatorial and NP-hard, and finding a globally optimal solution for this problem has exponential complexity. Therefore, the $$\mathcal{l}_0$$-norm is approximated by the $$\mathcal{l}_1$$-norm. Simulation results show that by locating the UAV using the proposed algorithm the overall performance of the network increases.

In the second approach, the UAV positioning problem is solved using an MAB framework. In this case, a simple scenario where only one source node is communicating with the relay to transmit its message to the base station is considered. Given the location of the source node and the predefined locations of the UAV, the MAB algorithm can successfully identify the optimal location for the UAV so the system achieves the maximum possible sum rate. The Greedy, ϵ-Greedy, and upper confidence bound (UCB) algorithms are used to solve the problem. The comparison of these algorithms based on their regret values reveals that the UCB algorithm outperforms the performance of the other algorithms. Simulation results show that the UCB algorithm can successfully identify the optimal location for the UAV to maximize the sum rate of the communication links.

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