The Study On Resource Management In 5G Heterogeneous Wireless Networks

To accommodate the explosive growth of user traffic demands and data needs,5G proposed a heterogeneous network architecture based on Ultra Dense Network(UDN).The intensive deployment of network nodes has brought tremendous gains for mobile communication network capacity.However,there are still many new problems to be solved in the UDN heterogeneous architecture.How to allocate spectrum resources rationally will directly affect the overall performance of the system.Therefore,It is of great significance to study the resource management and allocation of heterogeneous wireless networks.The paper focuses on the problem of frequency resource management and allocation of heterogeneous wireless networks in UDN.In order to improve the throughput of the system,an adaptive frequency planning scheme is proposed,based on the different clustering targets,can be divided into throughput adaptive frequency planning algorithm(TAFP)and interference adaptive frequency planning algorithm(IAFP).First,the cells is divided into two clusters based on interference reduction or throughput improvement,and then builds the mathematical model and solve the best spectral multiplexing threshold(TH).Finally,according to the SINR of the users,each user is allocated the corresponding Spectrum resources.Through MATLAB simulation platform,we make a careful comparative analysis and study with cell non-clustering and IAFP and TAFP.The simulation results show that,compared with non-clustering,the adaptive frequency planning scheme can significantly improve the edge performance of the system under different user distributions;Compared with the TAFP,IAFP can improve the edge gain of the system and show a good performance gain in the case of fewer users.In addition,the TAFP can also greatly improve the edge gain of the system.It has better performance when the number of users in a cell is large,the distribution of users is poor,and the SINR value is lower;However,both algorithms perform poorly when the distribution of users in center.Therefore,although the adaptive frequency planning algorithm can greatly improve the system performance when the distribution of users in edge,there is on gain when the user distribution is better.In the future,the adaptive frequency planning algorithm needs to be optimized to further improve the overall performance of the system.