Research On Multi-user Handover And Resource Management Strategy For LEO Satellite System

The Low Earth Orbit(LEO)satellite system has many advantages such as long communication distance and wide coverage.It plays an important role in emergency communications and disaster warning.In particular,it can effectively make up for blind areas such as remote mountainous areas and oceans that can't be served by terrestrial base stations.However,the high-speed movement of LEO satellites will cause frequent passive handovers for terminal users which affects the quality of communication services of the terminals.Secondly,the limited resources on the satellites restrict the capacity of the LEO satellite system.Therefore,this thesis focuses on the handover management and resource management of the LEO satellite communication system.The research works and innovations of the thesis are included as follows:1.Aiming at the problem of network congestion caused by concurrent handover of user groups in the LEO satellite system under the user aggregation scenario,a handover management strategy based on user grouping for multi-beam LEO satellite system is proposed.Firstly,a group handover management mechanism is designed based on the established multi-beam coverage model.In the member selection process,the handover trigger moment and the best beam are considered,and the users with similar handover behaviors are selected into a group to reduce system signaling cost.Then,the complete handover strategy is designed in detail from three aspects: clustering processing,group handover,and resource release.Finally,the signaling interaction process and message format for the cross-satellite and cross-beam handover mechanism are designed respectively,and the LEO satellite system simulation platform is built based on OPNET.The simulation results show that compared with the traditional independent handover scheme,the proposed strategy can reduce the system signaling overhead by 38.78% and the average handover delay by 13.46% on average,and increase the handover success rate by 2.82%.And when the number of users gathered is larger,the performance is more obvious.2.Aiming at the optimization of resource management methods caused by the limited resources and the dynamics of the network under the LEO satellite system,this thesis proposes a multi-beam LEO satellite system resource allocation algorithm based on Power Domain-NOMA(PD-NOMA).Firstly,under the constraints of the satellite transmission power and the user quality of service(Qo S),the algorithm considers both intra-beam and inter-beam interference.At the same time,the algorithm establishes a stochastic optimization model which aims to maximize the system throughput by subchannel allocation and power allocation jointly.Secondly,in order to solve the continuity and high-dimensionality of the state and action space,the model is turned into an MDP problem.and a resource allocation algorithm based on improved deep reinforcement learning is proposed to obtain the approximate optimal strategy.Finally,according to the difference of the state value function,the exploration rate of the action can dynamically adjust.Moreover,a dual experience playback pool is set to accelerate the learning process of the neural network.The simulation results show that the proposed algorithm can accelerate the convergence of the neural network and improve the system throughput by46.47% on average under the constraints of different transmit power and transmission rate.