Research On Pilot Allocation And Channel Estimation In Ultra-dense Networks

In recent years,with the rapid development of mobile Internet and Internet of Things,various emerging media services have followed one after another,including ultra-high-definition video media,webcasting and cloud computing and other functional applications,which have great demand for data traffic have become widespread.The continuing growth of terminal devices connected to wireless communication networks in the future will lead to exponential growth in data traffic.Therefore,people expect that next-generation wireless networks need to provide high-speed,low-latency,and high-reliability to meet various new services and application scenarios.In this situation,Ultra-Dense Network(UDN)technology has received widespread attention,and it is an important one of the many important technologies of 5G.UDN is mainly about using the dense deployment of micro base stations or Access Points(AP)to make the terminal closer to the AP so that it may reduce power consumption,avoid time delay,and achieve the improvement performance and system capacity.Therefore,research on related technologies of ultra-dense wireless communication networks has become an urgent concern for researchers and practitioners in the current communication-related fields.Ultra-dense networks can significantly increase network capacity.However,due to the distributed nature of micro base stations,APs and users,it will be difficult to predict the interference.Any network access node or user may experience strong interference or become a strong interference,and interference has always been an important reason that affects the improvement of system performance.Therefore,this article mainly analyzes and studies the methods of mitigating interference from two aspects,including the research of pilot allocation methods and channel estimation methods.To solve the pilot contamination problem in ultra-dense networks,this paper proposes a pilot allocation method based on user clustering;and from the aspect of channel estimation,combined with the sparse characteristics of channels in ultra-dense network systems,a method based on orthogonal matching is proposed.Improved channel estimation algorithm for Orthogonal Matching Pursuit(OMP).The main content of the research and results of the thesis are as follows:First,the paper analyzes and summarizes the common pilot allocation schemes in ultra-dense networks,such as greedy algorithm and graph theory coloring method,combines with the direct connection relationship between users and base stations,a distribution scheme based on user clustering is proposed,with the goal of minimizing the impact of users with greater potential interference.According to the signal intensity between the user and the base station,determine the main base station of each user,and calculate the degree of each main base station based on this,then arrange them in descending order.The users served by each base station are clustered in turn,based on the relationship between the size of the base station and the maximum number of users that can be accommodated in the cluster,and the signal intensity between the user and the main base station serving the user in the cluster,select the user to add or delete to the cluster,so that the number of users in the cluster is not greater than the number of available pilot sequences,thereby reducing the impact of users with greater potential interference.The final simulation results show that the performance of the proposed scheme is better than other traditional allocation schemes and random allocation schemes,and it can balance the improvement of performance and the increase of complexity better.Secondly,from other research of channel estimation,channel estimation is also an important part of interference cancellation.This paper first analyzes and introduces common channel estimation algorithms such as Least Square(LS)algorithm,Minimum Mean Square Error(MMSE)and OMP.In ultra-dense network,due to the propagation path loss,it can be seen that most of the power received from the user in the system is provided by the base station or AP near the user.This indicates that some channels in the channel matrix are dominant,while other channel signals are very weak.Therefore,the channel matrix in an ultra-dense network can be regarded as a quasi-sparse matrix.Based on the interference cancellation and computational complexity of channel estimation in ultra-dense networks,combined with the sparse characteristics of channels in ultra-dense networks,this paper proposes an improved OMP channel estimation algorithm.Based on the basic idea of orthogonal matching pursuit algorithm,Channel estimation can be regarded as the process of channel reconstruction and recovery.After preprocessing the received signal,which has been iteratively calculated and matched with the channel information closest to the actual channel with using less system resources,the channel state information of the main channel can be restored approximately.The simulation results show that compared with the traditional MMSE algorithm,although the overall performance of the algorithm will not be as good as before,it can estimate the main high-gain channel information while reducing the complexity better.