In the satellite-ground fusion network,in order to reduce the delay and energy consump-tion of users'offloading computing tasks,a satellite edge offloading computing strategy based on deep Q-network(DQN)algorithm is proposed by combining the mobile edge computing(MEC)technology with the satellite-ground collaborative network.The MEC server is deployed at the edge of the satellite network,and the central processing unit(CPU)is set to be an intelligent agent that can interact with the surrounding environment,and the task offloading delay and energy consump-tion weighting and minimization problems are established.In order to solve the non-convex optimi-zation problem,it is converted to a Markov decision process,and the corresponding state space,re-ward function and strategy update function are established,and the optimal solution is found.Simu-lation results show that compared with the Q-learning strategy and the actor-critic(AC)strategy,the proposed strategy can effectively increase the average return of the system and reduce the sys-tem overhead.
mobile edge computinghigh earth orbit satellitelow earth orbit satellitedeep Q net-workMarkov decision processthe 6th generation of mobile communication system
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