Research On Handover Strategy In Low Earth Orbit Mobile Satellite Network

Satellite internet is a new type of communication network which combines satellite communications with the Internet and other information networks.Using geosychronons,medium and low orbit satellites,satellite internet can provide global real-time and seamless internet services to various users on land,sea and sky.Among them,low orbit satellites have been paid more attention due to their low signal loss and small transmission delay.Low Earth Orbit Mobile Satellite Systems(LEO-MSSs)is a satellite constellation composed of abundant low orbit satellites to achieve global coverage.In LEO-MSSs,satellites move around the earth at a high speed.Therefore,the topology of the satellite networks is flexible and changeable,and the visiable time of a single satellite to the ground is limited.Consequently,the handover problem in the LEO-MSS is one of the hot topics in current research.Firstly,based on the scenario where multiple users apply for handover at the same time and there are multiple satellites available,this paper takes into account the resource competition phenomenon among different users.In order to improve the handover success rate of the system,a multi-user handover algorithm based on the evolutionary game is proposed.The user handover problem can be analyzed by the evolutionary game model.All users applying for handover are the players,and the associated satellites are the available strategies.The user's revenue function is made according to the bandwidth available,the elevation angle of satellite,the service time of satellite,and handover processing time.In the evolutionary game model,the user adjusts it strategy by comparing the current strategy revenue with the average revenue of all users,and finally the system reaches an equilibrium state,achieving the goal of user fairness.The simulation results prove that the proposed algorithm can effectively reduce the system handover failure rate and balance the network load at the same time.Then,aiming at the problem of high switching failure rate caused by high speed movement of user terminal and time-varying network topology,with the goal of maximizing the user quality of experience,the paper further put rorward a handover decision algorithm based on the Q-learning.Firstly,this paper uses GM(Gauss-Markov)model to predict the behavior of terminal,and then combines satellite ephemeris information to obtain the user's possible handover path fugure.Finally,the handover problem can be solved by reinforcement learning method.The algorithm describes the characteristics of candidate satellites as the system state,the satellites that the user can associate with represent the system's action set,and the service experience that users can obtain by linking different satellites is defined as the revenue function of the system.The optimal handover decision can be obtained according to the cumulative maximized rewrad.The simulation results prove that the proposed algorithm can effectively improve the success rate of system handover,and decrease the reduce the blocking rate of new calls.