Performance Optimization For UAV-enabled Wireless Networks With Underlaid D2D Communications

Compared with conventional static base stations,Unmanned aerial vehicle(UAV)enabled base stations can be deployed more swiftly and improve system performance by dynamically adjusting locations.And device-to-device(D2D)communication technology can be combined to extend the wireless coverage of UAV-assisted access networks.However,the limited energy and high mobility of UAV also bring a series of challenges.In order to improve the performance of UAV-enabled wireless networks with underlaid D2D communications,this thesis proposes a joint optimization scheme and two new optimization algorithms for different network models.The main contents and innovations are listed as below:A novel algorithm named user association based on linear programming algorithm(UA-LPA)is proposed.For the system model of UAV-assisted network combined with D2D technology,the wireless coverage is extended by establishing D2D communication links within ground users.A joint optimization scheme is raised to jointly optimize the system performance indicators such as throughput and wireless coverage.By iteratively optimizing the user association set,the weighted sum of rate and coverage is maximized.The system throughput and wireless coverage for difference schemes are compared and analyzed through simulations.The simulations also show the superiority of the proposed algorithm.A novel algorithm named power control based on interior point method algorithm(PC-IPMA)is proposed to solve the interference problem.For another system model of UAV-assisted networks with underlaid D2D communications,the throughput of D2D network is maximized by iteratively optimizing the transmission power of UAV and D2D transmitters.Simulation results show the advantage of the proposed algorithm compared with the difference of two convex functions(DoC)algorithm in terms of computational complexity,optimization of system performance indicators,etc.