Research On Key Technologies Of Joint Resource Optimization In Ultra Dense Networks

With the rapid development of Internet applications and intelligent devices,the user demand for network capacity and data rate become more and more higher,the fifth generation mobile communication system(5G)came into being.5G will realize the superiority in the aspects of data transmission rate,network capacity,coverage,delay,confidentiality,energy saving and so on.Ultra Dense Network(UDN),as an effective solution to the network,has become one of the key technologies of 5G communication.Ultra-dense network can effectively improve the network throughput,reduce the coverage of the blind area,and share part of the traffic load for the macro base station,which will achieve a load balance.However,the ultra-intensive deployment of the network is likely to cause serious interference,delay increase,network congestion and other issues,the joint optimization of wireless resources is the key to solve these problems.Aiming at the problem of capacity bottleneck in wireless network,a joint optimization model based on base station connection,channel assignment and power control is established,this thesis present an internal and external cyclic algorithm to solve the joint optimization model with an objective of maximizing the network sum rate and simultaneously guaranteeing the individual user quality-of-service,which ensures the fairness of users.Besides,the convergence and feasibility of the algorithm are analyzed.The simulation results show that the proposed algorithm has improved the network capacity by 30% compared with the traditional algorithm.Aiming at the problem of large delay and low energy utilization in the network,this thesis establishes a joint optimization model based on energy efficiency,delay and traffic allocation.The optimization goal is minimum network delay and power usage.A user connection algorithm based on energy aware and traffic aware is proposed to solve the joint optimization model.The algorithm consists of two parts: the user side algorithm and the base station algorithm.The simulation results show that the proposed algorithm can reduce the average traffic transmission delay by 36%.Aiming at the problem of traffic congestion in the network,this thesis establishes a joint optimization model based on traffic routing and power allocation.The optimization goal is the minimum total power consumption,which achieves greater network capacity and wider coverage at the lowest cost.At the same time,an improved routing method is proposed,which decomposes the network flow into several sub-network flows,allowing sub-network traffic to be transmitted on different paths,but the data is always transmitted between the same source and destination nodes.The simulation results show that the more nodes,the smaller the total power consumption of the network.