Drones are increasingly employed in several application domains thanks to their inherent versatility. This work envisions a scenario in which a swarm of Unmanned Aerial Vehicles (UAVs) enables the communication between a set of Sensor Nodes (SNs) and a control center. Considering a general fading channel model, a Mixed-Integer Non-Linear Programming (MINLP) problem is formulated to maximize the overall amount of relayed data by jointly optimizing trajectory and scheduling plan of each drone. Combining convex optimization and Ant Colony Optimization (ACO) algorithm, a quasi-optimal solution is obtained. Finally, numerical results demonstrate the effectiveness of the proposed solution in different parameter configurations and with respect to a benchmark algorithm.
Drone swarm as mobile relaying system: A hybrid optimization approach / Iacovelli, G.; Grieco, L. A.. - In: IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. - ISSN 0018-9545. - 70:11(2021), pp. 12272-12277. [10.1109/TVT.2021.3114677]
Drone swarm as mobile relaying system: A hybrid optimization approach
Iacovelli G.;Grieco L. A.
2021-01-01
Abstract
Drones are increasingly employed in several application domains thanks to their inherent versatility. This work envisions a scenario in which a swarm of Unmanned Aerial Vehicles (UAVs) enables the communication between a set of Sensor Nodes (SNs) and a control center. Considering a general fading channel model, a Mixed-Integer Non-Linear Programming (MINLP) problem is formulated to maximize the overall amount of relayed data by jointly optimizing trajectory and scheduling plan of each drone. Combining convex optimization and Ant Colony Optimization (ACO) algorithm, a quasi-optimal solution is obtained. Finally, numerical results demonstrate the effectiveness of the proposed solution in different parameter configurations and with respect to a benchmark algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
