Optimal Data Transfer in UAV-Assisted Edge-Networks Using 3D Beamforming

Reliable and low-latency data transfer to the cell edge users (CEUs) of 5G edge-network is a challenging problem. Solution to this problem can enable real-time applications such as remote health-monitoring of patients and target tracking in battle field. In this work, a novel method for optimal data transfer over UAV-assisted edge-networks is proposed. The proposed method utilizes unmanned aerial vehicle (UAV) as a relay node for data transfer between ground base station (GBS) and the CEUs. Additionally, UAV node is designed to be able to perform 3D beamforming leading to improved signal to interference noise ratio (SINR) and high throughput. To obtain optimal data transfer, the CEUs are first geographically clustered using a distance criterion. Subsequently, a joint optimization problem that aims to find the UAV trajectory and the beamforming downtilt angles, while applying minimum latency and maximum throughput constraints is formulated. This joint optimization problem is solved by using an iterative approach. Extensive simulations are then performed to validate this method for network latency and throughput under varying network conditions. The results are motivating enough for the method to be used in medium and large scale edge networks.