Research On Content Caching Based Cell Selection In Heterogeneous Small Cell Network

In recent years, in order to cope with the challenges brought by the explosive growth of mobile data traffic, 5G mobile communication has become a popular research direction in academia and industry, which makes the network to deal with massive information fast, efficiently, and in lower energy consumption. Benefitting from its high capacity, easy deployment, low power consumption and low cost, heterogeneous small cell network is one of the key technologies in 5G. However, it is also facing the problems of severe interference, load imbalance, limited wireless backhaul and so on.Content caching-aware heterogeneous small cell network can effectively solve the problems. The architecture enables content to be cached in advance from the content provider to the small-cell base station so that the users can obtain the content directly from the base station. This can reduce the load of the wireless backhaul, users' access latency, system energy consumption, and ultimately enhance the users' service experience.Under this background, it is important to study how to cache the content and how to select the access network for the users, so as to meet the high capacity and low energy consumption requirements of the network and the QoS requirements of users.In this paper, the above problems are studied, and the main works are as follows:Firstly, we propose a green and energy-saving cell selection scheme based on the content caching in heterogeneous small cell network. The implementation includes the following aspects: first, the key factors affecting the energy consumption of heterogeneous small cell network based on content caching are analyzed. Second, under this scenario, the problem of joint content cache placement and user access network selection is mathematically modeled. In the modeling process, the users'content requirements are taken into account with the objective to minimizing the system energy consumption. At last, a green and energy-saving cell selection scheme based on quantum behavior particle swarm optimization (QPSO) is proposed. The simulation result shows that the proposed scheme can minimize the energy consumption of the system while guaranteeing the users' content requirements.Secondly, we propose a user clustering access strategy which takes the content caching and low latency transmission guarantee into consideration. The implementation includes the following aspects: first, the main problems related to content transmission delay are analyzed in heterogeneous small cell network. Second, the problem of access network selection based on similarity of users' content requirements is mathematically modeled under the scenario of content-aware heterogeneous small cell network communication. In the phase of modeling, the base station adopts the multicast mode and considers the similarity of users' content requirements to cluster users, and takes the total system delay as the optimization target. Finally, based on the Kuhn-Munkras algorithm in graph theory, a user clustering access strategy with content caching and low latency transmission guarantee is proposed.Simulation result shows that the proposed strategy can minimize the total delay of the system and guarantee the users' content demand, and improve the users' experience.