Research On Resource Allocation Methods In OFDM System For LEO Satellite

With the extension of the global Internet and Internet of things services,the demand for social communication is growing.Satellite communications have many advantages over terrestrial networks,and becomes the effective complement of the territorial communication network.Low-Earth-Orbit satellite communication system has the advantages of high flexibility,easy deployment,high frequency of data update,low transmission delay and low construction cost.Therefore,the integration of LEO satellite and territorial 5G to build satellite-earth communication network has become an inevitable trend of communication development.The structure integration is the design goal of the current territorial 5G and satellite communication integration.As the basic transmission structure of5 G,Orthogonal Frequency Division Multiplexing(OFDM)technology used in resource scheduling can optimize the performance and benefit of satellite communication system.But considering the difference between satellite communication network and territorial cellular network,the application of OFDM technology in LEO satellite communication system is also faced with many challenges,such as the transient variability of satellite-earth channels,the uneven distribution of services in space-time,the limited resources on the satellite,the low processing capacity of satellite-borne equipment,and the excess Doppler effect.Based on the above background,proposes the research on resource allocation methods in OFDM system for LEO satellite.The main work of the paper includes:Due to the difference between satellite communication system and terrestrial cellular communication system,OFDM waveform scheme needs to be changed in the process of satellite and5 G communication system integration.By referring to the time-domain and frequency-domain resource allocation methods of 5G and combining the duration of the cyclic prefix inserted in OFDM,the OFDM symbol frame structure is adjusted.In the scenario of high-speed movement of LEO satellites,the Doppler frequency shift caused by the terminal elevation angle is calculated,and the OFDM carrier-to-carrier interference problem caused is analyzed.In order to balance the impact of Doppler frequency offset and system bandwidth utilization,the Shannon formula is used to calculate the theoretical system capacity of LEO satellites,and different subcarrier configurations are designed for simulation verification.A dynamic resource allocation strategy for OFDM in LEO satellites is proposed,which is based on the characteristics of LEO satellites such as high dynamics,channel characteristics,time-varying traffic and large Doppler effect.The sub-carrier allocation and power allocation are carried out successively.Before sub-carrier allocation,it guarantees the transmission performance of the channel by eliminating the sub-channels,reduces the cycle times of allocation by clustering multiple levels,and then distributes sub-carriers greedily according to the users’ requirements and channel characteristics,finally,the principle of water injection is applied to the power allocated in proportion to a single user.Simulation results show that the algorithm can adapt to LEO satellite scenarios and reduce the complexity of the algorithm,improve the system bandwidth utilization,ensure the fairness of user demand and transmission rate.At the same time,by introducing the concept of quality of user experience(Qo E),a multi-service oriented OFDM resource allocation algorithm is designed.According to the user experience evaluation method,the Qo E evaluation models are established,which can fit the data,voice and video service different characteristics of the users.Then,an optimization objective function model is established based on the minimum Qo E threshold for all users and the requirement of maximizing the average Qo E of the system.Considering the characteristics of OFDM multicarrier,the existing resource allocation scheme is improved to maximize the system transmission rate.The simulation results show that the proposed algorithm can not only improve the quality of user experience,but also improve the bandwidth utilization of the system efficiently.