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Drone base station (DBS) is a promising technique to extend wirelessconnections for uncovered users of terrestrial radio access networks (RAN). Toimprove user fairness and network performance, in this paper, we design 3Dtrajectories of multiple DBSs in the drone assisted radio access networks(DA-RAN) where DBSs fly over associated areas of interests (AoIs) and relaycommunications between the base station (BS) and users in AoIs. We formulatethe multi-DBS 3D trajectory planning and scheduling as a mixed integernon-linear programming (MINLP) problem with the objective of minimizing theaverage DBS-to-user (D2U) pathloss. The 3D trajectory variations in bothhorizontal and vertical directions, as well as the state-of-the-art DBS-relatedchannel models are considered in the formulation. To address the non-convexityand NP-hardness of the MINLP problem, we first decouple it into multipleinteger linear programming (ILP) and quasi-convex sub-problems in which AoIassociation, D2U communication scheduling, horizontal trajectories and flyingheights of DBSs are respectively optimized. Then, we design a multi-DBS 3Dtrajectory planning and scheduling algorithm to solve the sub-problemsiteratively based on the block coordinate descent (BCD) method. A k-means-basedinitial trajectory generation and a search-based start slot scheduling areconsidered in the proposed algorithm to improve trajectory design performanceand ensure inter-DBS distance constraint, respectively. Extensive simulationsare conducted to investigate the impacts of DBS quantity, horizontal speed andinitial trajectory on the trajectory planning results. Compared with the staticDBS deployment, the proposed trajectory planning can achieve 10-15 dB reductionon average D2U pathloss, and reduce the D2U pathloss standard deviation by 68%,which indicate the improvements of network performance and user fairness.

Multi-Drone 3D Trajectory Planning and Scheduling in Drone Assisted Radio Access Networks