In this paper,an Unmanned Aerial Vehicle(UAV)-enabled two-way relay system with Physical-layer Network Coding(PNC)protocol is considered.A rotary-wing UAV is applied as a mobile relay to assist two ground terminals fo...In this paper,an Unmanned Aerial Vehicle(UAV)-enabled two-way relay system with Physical-layer Network Coding(PNC)protocol is considered.A rotary-wing UAV is applied as a mobile relay to assist two ground terminals for information interaction.Our goal is to maximize the sum-rate of the two-way relay system subject to mobility constraints,propulsion power consumption constraints,and transmit power constraints.The formulated problem is not easy to solve directly because it is a mixed integer non-convex optimization problem.Therefore,we decompose it into three sub-problems,and use the mutation arithmetic of the Genetic Algorithm(GA)and Successive Convex Approximation(SCA)to dispose.Besides,a high-efficiency iterative algorithm is proposed to obtain a locally optimal solution by jointly optimizing the time slot pairing,the transmit power allocation,and the UAV trajectory design.Numerical results demonstrate that the proposed design achieves significant gains over the benchmark designs.展开更多
This paper introduces an innovative approach to address the trajectory optimization challenge for cellular-connected unmanned aerial vehicles(UAVs)operating in three-dimensional(3D)space.In most cases,optimizing UAV t...This paper introduces an innovative approach to address the trajectory optimization challenge for cellular-connected unmanned aerial vehicles(UAVs)operating in three-dimensional(3D)space.In most cases,optimizing UAV trajectories necessitates ensuring reliable network connectivity.H.owever,achieving dependable connectivity in 3D space poses a significant challenge due to terrestrial base stations primarily designed for ground users.Additionally,UAVs possess network information only for the areas they have visited,with global network information being inaccessible.To address this issue,we propose a collaborative approach in which multiple UAVs create a global model of outage probability using federated learning,enabling more precise and effective trajectory design.Building upon the constructed global information,we conduct the trajectory design.Initially,we introduce A-star(A*)algorithm for trajectory design in small-scale scenarios.Nevertheless,recognizing the limitations of A*algorithm in large-scale scenarios,we further introduce improved rapidly-exploring random trees(RRTs)algorithm for weighted path optimization.Simulation results are provided to validate the effectiveness of the proposed algorithms.展开更多
基金supported in part by the National Natural Science Foundation of China (61703197, 62061027).
文摘In this paper,an Unmanned Aerial Vehicle(UAV)-enabled two-way relay system with Physical-layer Network Coding(PNC)protocol is considered.A rotary-wing UAV is applied as a mobile relay to assist two ground terminals for information interaction.Our goal is to maximize the sum-rate of the two-way relay system subject to mobility constraints,propulsion power consumption constraints,and transmit power constraints.The formulated problem is not easy to solve directly because it is a mixed integer non-convex optimization problem.Therefore,we decompose it into three sub-problems,and use the mutation arithmetic of the Genetic Algorithm(GA)and Successive Convex Approximation(SCA)to dispose.Besides,a high-efficiency iterative algorithm is proposed to obtain a locally optimal solution by jointly optimizing the time slot pairing,the transmit power allocation,and the UAV trajectory design.Numerical results demonstrate that the proposed design achieves significant gains over the benchmark designs.
基金supported in part by the National Natural Science Foundation of China under Grant 62261035 and Grant 62061027in part by Jiangxi Science and Technology Foundation under Grant 20182ABC28008,Grant 20223BCJ25016,Grant 20213AAE01007,Grant 20224BBC31001,Grant 20223BBE51035,and Grant 20231ZDE04029。
文摘This paper introduces an innovative approach to address the trajectory optimization challenge for cellular-connected unmanned aerial vehicles(UAVs)operating in three-dimensional(3D)space.In most cases,optimizing UAV trajectories necessitates ensuring reliable network connectivity.H.owever,achieving dependable connectivity in 3D space poses a significant challenge due to terrestrial base stations primarily designed for ground users.Additionally,UAVs possess network information only for the areas they have visited,with global network information being inaccessible.To address this issue,we propose a collaborative approach in which multiple UAVs create a global model of outage probability using federated learning,enabling more precise and effective trajectory design.Building upon the constructed global information,we conduct the trajectory design.Initially,we introduce A-star(A*)algorithm for trajectory design in small-scale scenarios.Nevertheless,recognizing the limitations of A*algorithm in large-scale scenarios,we further introduce improved rapidly-exploring random trees(RRTs)algorithm for weighted path optimization.Simulation results are provided to validate the effectiveness of the proposed algorithms.
