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There has been a lot of research in the last decade on UAV assisted wireless communication networks. Due to its ability of fast deployment, it is seen as a potential solution to establish communication under emergency scenarios like natural disasters. The mobile nature of the UAVs offers a lot of flexibility, which can be harnessed to improve the QoS of a wireless communication network. In this paper UAV assisted cooperative communication to serve different user clusters distributed in a geographical location is considered. These user clusters do not have access to any conventional base station which is typically a scenario under natural disasters. Each cluster is served by two types of UAVs: cluster UAV which hovers on the top of the cluster centroid and relay UAV which relays information between a central base station (CBS) and cluster UAV. To achieve the required QoS, which is serving a maximum number of users with limited available power, two major parameters have to be optimized apart from other parameters. These are the height of the cluster UAV and trajectory of the relay UAV. To solve this problem, a three-step approach is considered in this paper. In the first step, an unsupervised learning algorithm is used to find the horizontal location parameters of cluster UAVs. Then using convex optimization to find the optimal height of the cluster UAV under power constraints and capacity requirement. Finally using a heuristic algorithm to find the optimal trajectory with minimum distance to be traveled by the relay UAVs. The wireless channel considered here is a simple line of sight (LoS) with a path loss. Computer simulations are performed to prove the validity of the proposed approach in comparison with random deployment. |
