Research On Computing And Network Resource Allocation Technology Of UAV Communication System

With the development of wireless communications,wireless networks are increasingly required to support high-throughput,ultra-reliable,low-power consumption,and architectures that support diverse applications.However,past research work has mainly focused on traditional network architectures with only fixed infrastructure,such as ground base stations(Base Stations,BSs),access points(Access points,APs),and fixed relays,which are difficult for traditional communication networks to pass.A cost-effective way to meet the increasingly diverse needs of users.In recent years,unmanned aerial vehicle(UAV)has become a research hotspot in wireless communication systems because it can provide flexible communication links from the air.UAV has a high degree of flexibility and rapid deployment capabilities,and can provide flexible and efficient services for emergency communications and disaster relief.The UAV-assisted wireless network can greatly improve the system performance by dynamically adjusting the position,thereby overcoming the related defects caused by the fixed traditional wireless communication architecture.This paper studies the problem of computing resource allocation in UAV-assisted Mobile Edge Computing(MEC)networks and network resource allocation in cognitive radio(CR)communication scenarios.The specific contents are as follows:(1)In the UAV-assisted mobile edge computing network,in order to improve the offloading efficiency,the tradeoff between computing bits and computing energy efficiency is studied,and the CPU frequency,transmit power,offloading time and UAV's trajectory are combined optimization.This problem is a non-convex optimization problem and it is difficult to solve,so an iterative algorithm is proposed,and the closed expressions of CPU frequency,transmit power and offloading time are derived.Simulation results show that,compared with the benchmark scheme,the proposed resource allocation scheme can achieve good tradeoff between the computing bits and the computing efficiency.(2)In the UAV-enabled cognitive radio network,in order to maximize the average achievable rate of cognitive UAV,a robust allocation algorithm for cognitive radio is proposed.In the system,the location information of the ground users is uncertain.By jointly designing the trajectory and transmit power of the UAV,and using the UAV mobility constraints,the average transmit power and the peak transmit power constraints of cognitive UAV,and the interference power constraints received by the primary user to formulate the maximum rate problem.This problem is non-convex,and an iterative algorithm is proposed to solve it.Simulation results show that the proposed scheme can improve the system performance compared with the benchmark scheme without robust design.