Resource Allocation And Trajectory Optimization For UAV Communication Systems

With the rapid development of modern mobile communication technologies,new business continue to emerge,such as the Internet of Things(Io T).The diversification of communication scenarios has brought huge opportunities and challenges to existing wireless communication systems.Traditional communication infrastructure is usually susceptible to the constraints of high deployment cost and fixed location.The aerial communication platform built with unmanned aerial vehicle(UAV)has outstanding advantages,such as rapid deployment,line-ofsight(Lo S)channels and high mobility,which can flexibly adapt to complex communication environments and provide reliable services.The application of UAV in the Io T communication system can not only better meet the fairness of users,but also improve the energy transmission performance of the system by combining with simultaneous wireless information and power transfer(SWIPT)technology,which can solve the problems of limited battery energy of the Io T nodes and high cost of battery replacement.In addition,the use of UAV in relay communication systems can achieve node positioning and tracking services to cope with the unexpected situations where node locations are unknown.Based on the above scenarios,this article set to the following studies.(1)In the Io T communications,for the system resource allocation of the SWIPT communications and trajectory optimization of the UAV,a joint optimization algorithm with the goal of maximizing the system energy harvesting is proposed.In this paper,a rotary-wing UAV is used as mobile access points.Taking into account the low latency of information transmission,orthogonal frequency division multiple access(OFDMA)technology is implemented to multi-user access.Susceptible to the constraints of user-fairness and minimum data transmission rate,the optimization problem joined with communication resource allocation,power splitting coefficient adjustment and UAV trajectory optimization is formulated,achieving the goal of maximizing system energy collection.The joint optimization algorithm combines the block coordinate descent algorithm and the successive convex approximation(SCA)method to split the complex optimization problem into multiple sub-problems,and alternately solve sub-problems until the results converge.Finally,the feasibility and effectiveness of the proposed algorithm are verified through mathematical simulation.In addition,by analyzing the resource allocation of single node,a strategy of resource allocation is summarized.(2)For the problem of search trajectory optimization in UAV-relay communication scenarios,this paper proposes an RSS-based trajectory optimization algorithm.The algorithm is divided into two phases: in the first phase,the UAV estimates the node position by RSS and determine the heading;in the second phase,the RSS change rate is measured to fine-tune the heading.Finally,through mathematical simulation,the superiority of the method is proved.The optimized heading is more accurate,and the search trajectory is shorter,which can effectively reduce the flight energy consumption of the UAV,and can provide tracking services for mobile nodes.