Research On Dynamic Rate Allocation Approaches Of UAV Networks

With the continuous development of society,people put forward higher requirements for the capacity,access capability,and temporary deployment ca-pability of wireless networks.In recent years,the boom of low-cost unmanned aerial vehicles(UAVs)has allowed them to participate in the design of next-generation wireless networks both as a new type of network nodes and as an aerial base station.Compared with traditional terrestrial communication sys-tems,the high-speed three-dimensional movement and the flexible networking ability of UAVs pose new opportunities and challenges for the design of next-generation communication networks.Different from researches of traditional static or low-speed movement wireless networks,this thesis considers the dy-namics of the UAV networks,focuses on the two major scenarios of the UAV networks,namely,mission-driven UAVs and UAV-assisted communications.In these two scenarios,the dynamic rate allocation of the multi-UAV networks is studied.In view of the dynamics of the UAV networks,this thesis studies the mission-driven UAV real-time fire surveillance networks with fixed trajectory.Firstly,according to the specific demands of surveillance,the organization,distribution and mobility mode of the UAV fire surveillance network with layered network structure is proposed.Secondly,owing to the requirements of real-time com-munication and the dynamic change of the topology in the network,the problem is modeled as the network utility maximization problem based on the joint dy-namic allocation of the source/channel rate,and the original problem is solved based on the Lagrangian dual method.Finally,the simulation analysis shows that the network utility could be improved efficiently by the j oint source/channel rate dynamic allocation through flexible dynamic routing.Furthermore,by exploring the dynamics of the UAV network,this the-sis studies the UAV-assisted relay network with variable trajectory.At the be-ginning,the thesis models the problem as the network-wide dynamic sum rate maximization problem based on joint UAV-user matching and UAVs' trajec-tory planning,and decouples the modeled mixed integer non-convex optimiza-tion problem.For the UAV-user dynamic matching subproblem,the periodic swap matching algorithm based on utility is proposed,and for the UAV trajec-tory planning subproblem,the deep deterministic policy gradient(DDPG)algo-rithm is designed to solve the problem in continuous domain.Moreover,based on the continuity and slow variability of the UAVs' movement,a combined dynamic rate allocation algorithm is proposed based on the above-mentioned algorithms.Simulation shows that the proposed algorithm significantly im-proves the network-wide dynamic sum rate compared with the traditional static rate allocation.