Joint Optimization Strategies for Computational Offloading and Trajectory Control in UAV Networks
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.
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维普
