Abstract

Abstract
<p>Unmanned Aerial Vehicles (UAVs) have emerged as suitable platforms for transporting and positioning communications nodes on demand, including Wi-Fi Access Points and cellular Base Stations. This paved the way for the deployment of flying networks capable of temporarily providing wireless connectivity and reinforcing the coverage and capacity of existing networks anywhere, anytime. Several solutions have been proposed in the literature for the positioning of UAVs that act as Flying Access Points (FAPs). Yet, the positioning of Flying Communications Relays (FCRs) in charge of forwarding the traffic to/from the Internet has not received equal attention. A major challenge in flying networks is the UAVs endurance. Since the UAVs are typically powered by on-board batteries with limited capacity, whose energy is used for communications and propulsion, the UAVs need to land frequently for recharging or replacing their batteries, limiting the flying network availability. State of the art works are focused on optimizing both the flying network performance and the energy-efficiency from the communications point of view, but do not consider the energy spent for the UAV propulsion. Yet, the energy spent for communications is typically negligible when compared with the energy spent for the UAV propulsion.</p><p>In order to address the FCR UAV positioning and energy-efficiency challenges, we have proposed the Energy-aware RElay Positioning (EREP) algorithm. EREP defines the trajectory and speed of the FCR UAV that minimize the energy spent for the UAV propulsion. However, since EREP considers a theoretical radio propagation model for computing the minimum Signal-to-Noise Radio (SNR) values that allow to meet the FAPs traffic demand, this may lead to network performance degradation in real-world networking scenarios, especially due to the FCR UAV movement. In this article, we propose the Energy and Performance Aware relay Positioning (EPAP) algorithm. Built upon the EREP algorithm, EPAP defines target performance-aware SNR values for the wireless links established between the FCR UAV and the FAPs and, based on that, computes the trajectory to be completed by the FCR UAV, so that the energy spent for the UAV propulsion is minimized. EPAP was evaluated in terms of both the flying network performance and the FCR UAV endurance, considering multiple networking scenarios. Simulation results show gains up to 25% in the FCR UAV endurance, while not compromising the Quality of Service offered by the flying network.</p>

Abstract

Abstract

Abstract
5G has become increasingly popular nowadays, mainly due to its characteristics which enable high data rates and low latency. At the same time, mobile robotic platforms, such as drones and robots, appeared as suitable platforms to carry radio stations, enabling the on-demand placement of 5G communications cells. The main contribution of this paper is an obstacle-aware on-demand 5G network. The proposed solution consists of a 5G radio station (gNB) carried by a mobile robotic platform capable of providing obstacle-aware wireless connectivity to 5G User Equipments (UEs), leveraged by a novel virtual network function - On-Demand Mobility Management Function (ODMMF). ODMMF is designed to integrate the 5G Core network and it allows to monitor the radio conditions provided to the served UEs, while enabling the positioning of the mobile robotic platform remotely by taking advantage of the visual information provided by on-board video cameras. The proposed solution was validated using an experimental prototype, under a representative networking scenario. © 2022 IEEE.