Research On Energy Consumption Minimization For Air-Ground Cooperation Covert Mobile Edge Computing System

With its high mobility,low cost and high flexibility,unmanned Aerial Vehicle(UAV)has received more and more attention in wireless communication networks.First of all,because of the high flexibility and mobility,UAVs can reduce the impact of buildings or shelters on the communication quality by adjusting the flight height,so as to establish a good air-to-ground(A2G)line-of-sight channel with the ground.Secondly,air-ground cooperation wireless communication network based on UAV can realize on-demand deployment in emergency,and is widely used in emergency communication and post-disaster rescue search.However,with the rapid development of wireless communication technology and the arrival of the era of artificial intelligence,UAVs need to deal with a large number of computationally intensive and delaysensitive tasks,which poses a challenge to their limited computing power.Mobile edge computing(MEC)can effectively solve the problem of limited computing power of UAVs by offloading computing tasks to edge cloud servers with rich computing resources.Moreover,due to the broadcasting,openness and line-of-sight channel,the wireless communication system based on UAV is more vulnerable to the attack of malicious eavesdroppers and warders,which poses a challenge to the security of the system.Covert communication can effectively solve the insecurity of wireless communication by taking advantage of the uncertainty of the gatekeeper,including the randomness of the channel state or the uncertainty of the noise power of the receiver,to design the information sent by the transmitter to achieve the purpose of covert communication.Meanwhile,due to the limited onboard battery energy of UAV,frequent charging or replacement of batteries will bring huge costs,so it is also very necessary to design an energy-saving wireless communication network based on UAV.Although making full use of the UAV’s mobility can lead a higher quality communication links by closer to the ground base stations(GBSs)and avoid detection for covert communication by further away from the warden node.However,this flight trajectory usually makes UAV generate higher flight propulsion energy consumption.In addition,the propulsion energy consumption is not in the same order of magnitude with communication energy consumption and offloading energy consumption.Therefore,this paper aims to minimize the weighted total energy consumption of UAV by reasonably optimizing the UAV flight trajectory,transmit power and other related variables to ensure the security of the communication system.The main work of is as follows:(1)Energy consumption optimization strategy for air-ground cooperation covert MEC system: facing the scenario that a rotary-wing UAV as an air user offloads the computing tasks that beyond its own computing capacity to the GBSs under the accurate position of a known warden node Willie.And in this process,the UAV needed to evade the detection of Willie.Our goal is to minimize the weighted total energy consumption of the UAV while satisfying a given covert rate.Since the target problem is mixed integer non-convex,an alternate iterative optimization algorithm based on block coordinate descent method and successive convex approximation method is proposed.The numerical results show that compared with other benchmark schemes,the proposed scheme can significantly reduce the total energy consumption of UAVs(2)Energy consumption optimization strategy for a robust air-ground cooperation covert mobile edge computing system: facing the scene that the accurate position information of the warden node Willie is difficult to obtain in practical application,we studied a energy consumption optimization strategy of robust air-ground collaborative covert mobile edge computing system.In the process of the UAV offloading the computing task to the GBSs,the warden node Willie,which can obtain the accurate position information of the UAV,trying to detect the offloading situation of the UAV through limited observation,and the UAV only knows the estimated position of Willie.In order to ensure robust covert communication,the covert constraints are analyzed from the perspective of the warden node Willie and the UAV,and then the weighted total energy consumption of the UAV is minimized through joint optimization calculation of the task allocation,the UAV-GBS association,the UAV power and the UAV flight trajectory.The numerical results show that the proposed scheme can converge quickly,and the transmission power and flight trajectory of the UAV can be reasonably designed to avoid the detection of the warden node Willie and achieve covert communication.In addition,compared with the non-robust algorithm,it is proved that the proposed robust algorithm can offload more computing tasks to the GBSs in unit time under the same covert constraints.