By fully exploiting the mobility of unmanned aerial vehicles (UAVs), UAV-based aerial base stations (BSs) can move closer to ground users to achieve better communication conditions. In this paper, we consider a scenario where an aerial BS is dispatched for satisfying the data request of a maximum number of ground users, weighted according to their data demand, before exhausting its on-board energy resources. The resulting trajectory optimization problem is a mixed integer non-linear problem (MINLP) which is challenging solve. Specifically, there are coupling constraints which cannot be solved directly. We exploit a penalty decomposition method to reformulate the optimization formulation into a new form and use block coordinate descent technique to decompose the problem into sub-problems. Then, successive convex approximation technique is applied to tackle non-convex constraints. Finally, we propose a double-loop iterative algorithm for the UAV trajectory design. In addition, to achieve a better coverage performance, the problem of designing the initial trajectory for the UAV trajectory is considered. In the results section, UAV trajectories with the proposed algorithm are shown. Numerical results show the coverage performance with the proposed schemes compared to the benchmarks.

Unmanned Aerial Vehicle (UAV) networks have recently gained interest, owing to the mobility of UAVs that can be exploited to improve channel conditions and user coverage. In this paper, we consider a scenario where a rotary-wing UAV is dispatched for covering a maximum number of ground users by jointly optimizing the UAV trajectory and bandwidth allocation, under constraints of predetermined maximal total flight time and on-board energy. The problem is difficult to solve since has nonconvex constraints and includes infinite variables over time. As such, we propose an iterative algorithm with guaranteed convergence by applying block coordinate descent and successive convex approximation techniques. We further exploit the path discretization to formulate the original problem into an optimization formulation with finite variables. We deploy a UAV circular trajectory as the benchmark. The numerical results show that the proposed algorithm significantly outperforms the benchmark scheme and the bandwidth allocation can improve UAV coverage compared with the UAV trajectory only with time partitioning. Index Terms-UAV communication, trajectory design, bandwidth allocation. I. INTRODUCTION Unmanned aerial vehicles (UAVs) provide wireless communication solutions in many real-world scenarios and thus gaining significant popularity in research [1], [2]. In one of their key use cases, UAVs can be applied as aerial base stations (BSs) and deployed in crowded areas to ease the burden of existing cellular systems [3], [4]. Moreover, the deployment of UAVs is also relevant in emergency or disaster scenarios where ground communication infrastructures are damaged [2], [5]. The authors in [6] studied the trade-off between altitude of static UAV and its coverage area. Algorithms were proposed to maximize coverage by multi-static UAVs deployment [7]-[10]. The work in [7] considered the effect of inter-cell interference. A research that focused on the coverage-efficient and energyefficient deployment of static UAVs by leveraging geometrical

We consider an unmanned aerial vehicle (UAV) based joint radar localization and communication system, where a UAV transmits the downlink signal to a ground communication user and the transmitted signal is also exploited to localize a target coordinates. We aim to optimize the UAV path with energy constraints. We formulate the trajectory design into a weighted optimization problem, where a scalable performance trade-off between localization and communication can be achieved. An iterative algorithm is exploited then to address the trajectory design formulation. Numerical results are provided to validate the effectiveness of the proposed UAV trajectory design approaches.

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Unmanned aerial vehicle (UAV) can work as a portable base station providing not only the communication service to ground users, but also the sensing functionality to localize targets of interests. In this paper, we consider a scenario with one rotary-wing UAV to transmit signals for a communication service and receive echos for a target estimation. We propose a multi-stage trajectory design method to jointly improve both the communication and sensing (C&S) performances. We formulate the trajectory design problem into a weighted optimization problem and propose an iterative algorithm to solve it. Numerical results show the performance trade-off between C&S.