Multiple UAVs Trajectory Optimization in Multicell Networks With Adjustable Overlapping Coverage

Trajectory optimization of unmanned aerial vehicles (UAVs) operating as flying base stations (FBSs) evolved a novel integration component in beyond 5G (B5G) networks and has recently received significant research attention. Notably, the vast majority previous mainly concentrated on case single terrestrial macro station (BS) which is used depot for multiple FBSs. In this article, we focus more general use where FBSs located at different macro-BSs serve ground users (GUs) cluster points (CPs). To end, formulate trajectory problem using mixed-integer linear programming (MILP) formulation with aim to minimize total travel time (TTT) multicell network their cell coverage or boundary adjustable deployment; creating that sense virtual cells Furthermore, heuristic algorithms are proposed provide competitive solutions reduce computational view curse dimensionality original problem. Numerical investigations reveal path planning decrease TTT increase efficiency offloading collected data deployment gains up approximately 23% 19%, respectively, compared nominal schemes consider predefined range no boundaries. Aside from above, previously strategies, achieve an almost 27% improvement terms fairness (Jain’s index) FBS traveling time.