Research On Ultra-Dense Networking Technology Based On Dynamic Clustering And User Access Control

With the arrival of the era of big data and the cloud,thousands of times of data growth has been brought.Large-scale mobile interconnection equipment access,cross the traditional meaning of“ubiquitous communication”.The existing communication network can no longer meet the current people's communication needs.Ultra-dense heterogeneous cellular network emerges as the times require.Ultra-dense heterogeneous cellular network is to deploy low-power small base stations intensively coverage area of existing macro base stations,and to highly reuse the existing spectrum resources,thus greatly improving the spectral efficiency in unit area and increasing network capacity.Intensive deployment of small base stations can effectively enhance coverage and system capacity,but it also leads to difficulties in allocation and management of unlimited resources.With the popularity of intelligent mobile terminals and user's demand for high quality of service,mobile traffic increases exponentially.In order to meet the growing demand for wireless communication services,ultra-dense network based on greater infrastructure node density and spatial frequency reuse are widely used.It is one of the key technologies to enhance the capacity of future wireless systems.However,high-density deployment not only enhances edge interference,but also affects user mobility management,which also causes irregular chandes in the coverage of each cell.In addition interference cancellation in ultra-dense networks is a key issue that attracts worldwide attention.Ultra-dense networking technology is one of the key technologies to solve this challenge.Interference alignment(IA)is considered to be an effective technique for optimal capacity scaling.However,in real communication system,alleviating all interference through interference alignment requires a lot of signaling overhead and high iteration complexity.1.In this paper,we propose a dynamic clustering algorithm based on graph partitioning with low complexity.Our work focuses on dividing the whole network into a number of clusters under size constraint and realizes the maximum intra-cluster interference and minimum intercluster interference.In addition,neighbor selecting scheme based on neighbor interference ratio in proposed algorithm can get the proper cluster result in the random spatial network model.Furthermore,proposed algorithm is compared with other traditional algorithms in complexity and performance.The simulation results show that proposed algorithm reduces the complexity of clustering process significantly and achieves higher performance gain than existing clustering algorithms.2.For the user access part,this paper first studies the user access strategy in ultra-dense heterogeneous cellular network,and then models the three-tier ultra-dense cellular network.In this model,the user access strategy based on multi-attribute decision-making is adopted to achieve user access.In the process of macro cellular modeling,Tyson polygons is used instead of traditional cellular hexagon to reflect the highly irregular deployment of network nodes.In the part of user access control algorithm,the optimal solution of user access is obtained by considering user access time loss,receiving power,signal-to-interference ratio and base station performance.In order to alleviate the ping-pong effect,the switching threshold is set to ensure the stable access of users under the same communication quality.