Computational offloading and trajectory control are mutually coupled in UAV networks,and joint design of these two aspects can enhance their overall performance.To this end,this paper investi-gates the joint optimization problem of computation task offloading and trajectory control with the objective of minimizing the delay and energy consumption of UAV systems.First,the problem is decomposed into a computation task offloading subproblem and a trajectory control subproblem.Then,a solution algorithm based on population diversity particle swarm optimization with multi-critic deep deterministic policy gradi-ent(PDPSO-MCDDPG)is proposed.The introduction of multi-critic(MC)networks in the DDPG framework mitigates the abnormal fluctuations caused by a single critic network,thus enable to achieve the optimal policy.Simulation results indicate that the proposed joint optimization strategy of computation offloading and trajectory control based on the PDPSO-MCDDPG algorithm can effectively reduce the pro-cessing delay and energy consumption of the UAV system.
维普
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