This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU...This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU's computational speed under the set of resource constrains.To this end,we first derive the energy consumption model of data processing,and then obtain the energy consumption model of fixed-wing UAV's flight.The optimization problem is mathematically formulated.To address the problem,we first obtain the approximate optimization problem by applying the technique of discrete linear state-space approximation,and then transform the non-convex constraints into convex by using linearization.Furthermore,a concave-convex procedure(CCCP) based algorithm is proposed in order to solve the optimization problem approximately.Numerical results show the efficacy of the proposed algorithm.展开更多
Recently, due to the deployment flexibility of unmanned aerial vehicles(UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assiste...Recently, due to the deployment flexibility of unmanned aerial vehicles(UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assisted mobile relay communication system is limited by the capacity of wireless backhaul link between base station and UAV. In this paper, we consider a caching UAV-assisted decode-and-forward relay communication system in a downlink maritime communication. For the general case with multiple users, the optimal placement of UAV is obtained by solving the average achievable rate maximization problem through the one-dimensional linear search. For a special case with single user, we derive a semi closedform expression of the optimal placement of UAV. Simulation results confirm the accuracy of analytical results and show that the optimal placement of UAV and the average achievable rate significantly depend on the cache capacity at UAV. We also show the difference between the performances of the air-to-ground model and the air-to-sea model.展开更多
基金supported in part by National Natural Science Foundation of China(Grant No.61702149,U1709220)
文摘This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU's computational speed under the set of resource constrains.To this end,we first derive the energy consumption model of data processing,and then obtain the energy consumption model of fixed-wing UAV's flight.The optimization problem is mathematically formulated.To address the problem,we first obtain the approximate optimization problem by applying the technique of discrete linear state-space approximation,and then transform the non-convex constraints into convex by using linearization.Furthermore,a concave-convex procedure(CCCP) based algorithm is proposed in order to solve the optimization problem approximately.Numerical results show the efficacy of the proposed algorithm.
基金supported in part by the Natural Science Foundation of China under Grant U1805262,61671251,61871446,61701118,61871131,and 61404130218the Natural Science Foundation of Fujian Province under Grant 2018J05101。
文摘Recently, due to the deployment flexibility of unmanned aerial vehicles(UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assisted mobile relay communication system is limited by the capacity of wireless backhaul link between base station and UAV. In this paper, we consider a caching UAV-assisted decode-and-forward relay communication system in a downlink maritime communication. For the general case with multiple users, the optimal placement of UAV is obtained by solving the average achievable rate maximization problem through the one-dimensional linear search. For a special case with single user, we derive a semi closedform expression of the optimal placement of UAV. Simulation results confirm the accuracy of analytical results and show that the optimal placement of UAV and the average achievable rate significantly depend on the cache capacity at UAV. We also show the difference between the performances of the air-to-ground model and the air-to-sea model.
