Research On Cell Association Scheme For Jointly Optimizing Content Acquisition And System Capacity

In recent years,with the rapid development of wireless network technologies such as Internet of Things and the fifth generation mobile communication system(5G),the number of terminals has grown exponentially and new types of communication services have emerged,which has led us to a big data era of Ultra-Dense Cellular Network(UDCN)and complex communications.5G is expected to achieve higher data rate,greater system capacity,lower latency,and better user service quality,while UDCN is one of its key features.Ultra-dense small cells(such as low-power picocells and femtocells)are effectively deployed on a large scale within the coverage of traditional high-power macro base stations,which improves the spectrum efficiency and shortens the distance between users and service base stations.Meanwhile,with the large-scale popularization of intelligent mobile terminals and wireless multimedia data services,the mobile data traffic has grown geometrically.Therefore,in future UDCN,how to select the most suitable base station for access and quickly obtain the required media content becomes an important research problem.This dissertation studies the joint optimization of content acquisition and system capacity,and a cell association scheme jointly optimizing single content acquisition and system capacity is proposed.The content acquisition hop count is incorporated in the capacity-based cell association scheme,so that the terminal can quickly acquire the content after associating with the corresponding cell.In order to reduce the number of content acquisition hops,we first designed a content deployment scheme based on greedy algorithm to deploy content in the base station.With the help of the virtual base station method,the traditional cell association problem is transformed into a 2-dimensional assignment problem hence the Hungarian algorithm is used to obtain the optimal solution.Simulation results show that the proposed scheme maximizes the utility function and greatly reduces the content acquisition hop count.In order to demonstrate the suitability of the proposed scheme for more scenarios,this dissertation further simulates the scenarios that contain multiple contents.Results show that similar conclusions are drawn as for the single-content scenarios,which indicates that the proposed scheme also works well for multiple-content scenarios.