Game Theory-based Association Problem Research In Heterogeneous Cloud Radio Access Networks

The Heterogeneous Cloud Radio Access Network is a kind of integrated network architecture,which can realize the efficient reuse of limited spectrum resources,reduce the infrastructure construction cost of base station,improve energy efficiency,and support unified scheduling management.With the rapid popularization of H-CRAN architecture,more and more attention has been paid to its existing problems,such as interference problems,scheduling problems,deployment problems,association problems and so on.In previous studies,less attention has been paid to the competition between users and the impact of unbalanced traffic in the network in the association strategy between users and base stations,which are easy to cause congestion and high delay in the network.In the study of mobility association problems,researchers generally lack of in-depth mining of users' mobile habits,which can easily lead to unnecessary handovers and reduce the transmission rate.Game theory is an effective way to optimize the configuration of communication.therefore,this thesis mainly aims at H-CRAN scenario,uses game theory tools to model the mechanism of user competition and the imbalance of traffic load,and designs matching game algorithm to dredge the congestion caused by user competition,reduce the network delay,improve the transmission rate.We deeply mine the mobility information of users,model the mobile behavior of users,design a matching game algorithm to avoid unnecessary handovers,to improve the transmission rate.The main research contents are as follows.(1)The user association mechanism under the condition of limited fronthaul capacity under complete information is studied.Firstly,the user achieved data rate and delay index are quantified,and the income preference function between the micro base station and the user is established,and then the bidirectional matching game model is established to solve the access problem,which can realize the traffic load balancing of micro-base station,reduce congestion,reduce delay and improve the transmission rate of users.(2)The user association mechanism of micro-base station based on speed and location information under complete information is studied.We consider the changes of user mobile state,establish the benefit preference function between micro-base station and users,and formulate a bidirectional matching game algorithm to obtain the best strategy of long?term benefit,reduce handover cost and improve the transmission rate of users.At the same time,we propose an online learning algorithm to learn the changes of user behavior and provide the basis for the implementation of long-term strategies.(3)The simulation results verify the rationality of the design of benefit preference function,and prove that the algorithm based on bidirectional matching game can improve the load balancing ability of communication system,reduce the number of handovers,and improve the transmission rate of users.