On The Optimization Of Resource Allocation For UAV-assisted SWIPT Systems

With the continuous development of new application scenarios of Internet of Things and the growing demand for communication,the amount of mobile terminal and data connected to the network is increasing exponentially,which puts forward higher requirements on the performance of wireless communication network.On the one hand,the mobile terminal and wireless nodes are mostly battery-powered,and the limited battery life has become a key factor which restrict the reliability of the communication network.Besides,the continuous growth of communication traffic has brought a huge energy consumption.In addition,with the increase of base stations and wireless nodes,the channel conditions become more complex,and the deployment of the network architecture also needs to be optimized.Therefore,how to improve the lifetime and energy efficiency of wireless communication network while ensuring its communication quality has become a key issue.By combining wireless information transfer and wireless power transfer,wireless powered communication network(WPCN)and simultaneous wireless information and power transfer(SWIPT)enable the device to transmit information and collect energy at the same time,which improving the endurance of mobile device and the energy efficiency of the network.On the other hand,based on its high flexibility,Unmanned Aerial Vehicle(UAV)can be quickly adjusted according to the needs of ground devices,showing great advantages in improving channel quality and real-time deployment.Therefore,comprehensively considering the advantages of SWIPT in improving energy efficiency and lifetime of mobile devices and the advantages of UAV in enhancing communication system performance,this paper investigates the resource allocation algorithm of UAV-assisted SWIPT system.The main contents of this article are as follows:1.The joint resource allocation problem of multi-UAV enabled WPCN is studied in order to maximize the minimum throughput.The model of multi-UAV enabled WPCN is constructed.Considering the energy constraints of ground equipment,UAV position constraints and time slot allocations,the resource allocation optimization problem for minimum throughput maximization was proposed.Due to the binary and couple variables and the interference signal,the proposed problem is mixed-integer non-convex,which is difficult to solve directly.A deep reinforcement learning based algorithm is proposed for a feasible solution.Numerical results verify the effectiveness of the proposed algorithm,and confirm the advantage of mobility and trajectory design of UAV.2.Joint resource allocation optimization problem is studied to maximize the minimum throughput of Intelligent Reflecting Surface(IRS)assisted UAV SWIPT system.Based the advantage of IRS in combating multi-path fading and improving the performance of communication system,IRS assisted UAV SWIPT system is constructed.Considering the downlink of the aforementioned system,a joint resource allocation problem is formulated to maximize the minimum throughput with the constraints of the maximum transmit power of UAV and the minimum energy requirement for energy harvesting devices.In order to deal with the throughput maximization problem of couple variables and non-convex,an iterative algorithm is proposed for joint optimization of resource allocation.Numerical results verify the effectiveness of the proposed algorithm.Besides,the simulation results indicate that the proposed IRS assisted UAV SWIPT system significantly improve performance gain in terms of minimum throughput maximization compared with the conventional UAV SWIPT system.