Wireless network coverage can be disrupted by unexpected events. Temporary connectivity can be necessary in regions that are outside of the wireless communication infrastructure. One solution to that is the use of Unmanned Aerial Vehicles (UAV) as mobile base stations. UAVs can act like temporary “range extenders” in unexpected or temporary events. Low Altitude Platforms (LAPs), like drones, are specific types of UAVs that can be used for range extension tasks. As the drones have limited energy for their operation, their deployment should be optimized to get maximum possible coverage of the desired region with the constraints related to the capability of the overall system. This study proposed a novel framework for optimum coverage of the desired region with given drones by using heuristic optimization methods. Multi-objective optimization considers minimizing overlapping regions between drones, overflowing regions for the drones (coverage outside of the desired region), and flight distance of the drones from/to the base station. The trade-offs among constraints are resolved by using priority based optimization in which by setting weights the user can prioritize one or more constraints over the others. © 2020, Springer Nature Switzerland AG.
Multi-objective Priority Based Heuristic Optimization for Region Coverage with UAVs
Mostarda L.
2020
Abstract
Wireless network coverage can be disrupted by unexpected events. Temporary connectivity can be necessary in regions that are outside of the wireless communication infrastructure. One solution to that is the use of Unmanned Aerial Vehicles (UAV) as mobile base stations. UAVs can act like temporary “range extenders” in unexpected or temporary events. Low Altitude Platforms (LAPs), like drones, are specific types of UAVs that can be used for range extension tasks. As the drones have limited energy for their operation, their deployment should be optimized to get maximum possible coverage of the desired region with the constraints related to the capability of the overall system. This study proposed a novel framework for optimum coverage of the desired region with given drones by using heuristic optimization methods. Multi-objective optimization considers minimizing overlapping regions between drones, overflowing regions for the drones (coverage outside of the desired region), and flight distance of the drones from/to the base station. The trade-offs among constraints are resolved by using priority based optimization in which by setting weights the user can prioritize one or more constraints over the others. © 2020, Springer Nature Switzerland AG.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
