Joint Optimization Of Cache-Enabled Uav Content Delivery And Trajectory

With the development of mobile communication technology and Internet of things,wireless communication equipment and wireless data traffic have increased explosively.In order to reduce the delay of users’content acquiring in networks and alleviate the network load,Mobile Edge Caching(MEC)technology was proposed and has received extensive attentions.MEC deploys the cache in the edge node of the network,so that users can directly obtain the required content from edge nodes such as base stations,reduce the delay caused by the transmission from the core network to users,and effectively improve the quality of user experience.Meanwhile,with the development of civil Unmanned Aerial Vehicle(UAV)industry,UAV assisted cellular network has also catched a lot of attentions in the industry.Due to more line of sight(LoS)links brought by UAVs,the mobility and flexibility of the UAVs,cache-enabled UAV assisted cellular network can better meet the needs of massive content deliveries in hot spot areas,has larger network capacity,better user experience and lower deployment cost.This work is supported by the National Natural Science Foundation"Research on Multilevel Cooperative Caching in UAV assisted Cellular Networks".The content delivery and UAV trajectory design in cacheenabled UAV assisted cellular network was investigated.In this work,two types of networks were investigated:single cache-enabled UAV assisted cellular network and multiple cache-enabled UAVs assisted cellular network.Their corresponding joint content delivery and UAV trajectory optimization algorithms were proposed respectively.Our work is summarized as follows:1)The literature on cache-enabled UAV assisted cellular network was reviewed.Firstly,we summarized the UAV assisted cellular network,introduced the basic concept and classification of UAV and the main application scenarios of UAV communication networks,summarized and analyzed the works on UAV’s air to ground channel model,UAV deployment and UAV flight trajectory design.Then the works on the mobile edge cache technology,including cache placement location,cache performance index and cache strategy classification and the literature survey on them were presented from the perspective of cache placement and content distribution.Finally,the characteristics and advantages of cache-enabled UAV assisted cellular network were discussed,and some important works related to this kind of network design were summarized.2)In single cache-enabled UAV assisted cellular network,to handle the timeliness requirements of content delivery and the limitation of communication resources,a jointly optimizing content delivery and UAV trajectory algorithm was proposed.Firstly,based on the analysis of network model and channel model,the problem was modeled as a problem of jointly optimizing content scheduling,power and bandwidth allocation and UAV trajectory.The objective was to minimize the completion time of UAV content delivery.To tackle the non-convexity of the problem,this thesis proposed a single UAV content delivery and trajectory joint optimization algorithm based on block coordinate descent(BCD).The original problem was divided into three subproblems:content scheduling,bandwidth and power allocation,and UAV trajectory optimization.The interior point method was invoked to solve the convex problems such as content scheduling,bandwidth and power allocation subproblems;The UAV trajectory optimization subproblem was converted to a convex form then solved.Finally each subproblem was optimized iterately until it converged.After that,the convergence and complexity of the algorithm was analyzed.Simulation results showed that compared to the benchmark algorithms,the proposed algorithm could effectively reduce the completion time of the content delivery misson.3)In multiple cache-enabled UAV assisted cellular network,to handle the timeliness requirements of content delivery,the limitation of communication resources and co-channel interference,a jointly optimizing content delivery and trajectory algorithm for multi-UAV was proposed.Firstly,based on the analysis of network model and channel model,the problem was modeled as a problem of jointly optimizing cache placement,content scheduling,power and bandwidth allocation and UAV trajectory.The objective was to minimize the completion time of UAV content delivery.To tackle the non-convexity of the problem,this thesis proposed a multi-UAV content delivery and trajectory joint optimization algorithm based on block coordinate descent(BCD).The original problem was divided into four subproblems:cache placement,content scheduling,bandwidth allocation and UAV trajectory optimization.For the 0-1 integer optimization problem of cache placement,we strictly proved that it is NP hard,and then regarded it as a many to many matching problem,which was then solved by matching exchange algorithm;The convex problems such as content scheduling and bandwidth allocation subproblem were solved by interior point method;The UAV trajectory optimization subproblem was converted to a convex form then solved as a convex problem.Finally each subproblem was optimized iterately until it converged.After that,the convergence and complexity of the algorithm was analyzed.Simulation results showed that compared to the benchmark algorithms,the proposed algorithm could effectively reduce the completion time of the content delivery misson.