Research On Satellite Time Domain Resource Allocation Scheme For Multi-tas

In the space-air-ground integrated network,satellite communication system plays an irreplaceable role with its advantages of wide coverage and good communication quality.With the continuous development of society,the user terminal increases sharply,while the available resources on board the satellite are extremely short,unable to meet the massive demands of users.Therefore,it is urgent to effectively integrate and allocate the limited resources to improve the satellite system performance.In view of above problems,this paper mainly studies the resource allocation in the communication scenarios of multi-beam satellite system and relay satellite system from the two aspects of time-frequency resource allocation and time-window resource allocation.In multi-beam satellite system,aiming at the problem of uneven spatial and temporal distribution of service requirements,a beam-hopping resource allocation algorithm based on service priority is proposed.By distinguishing different service requirements and user priorities,and considering the problem of co-channel interference,the sub-frame allocation model of beam-hopping is established to prioritize the transmission of high-priority services,so as to meet the requirements of each beam as far as possible.The simulation results show that,compared with traditional beam hopping algorithm,the algorithm can improve the success rate of high-priority service by 16.2%,better meet dynamic requirements of multi-user and multi-service,and provide targeted service guarantee for differentiated users and service.In tracking and data relay satellite system,considering the resource usage of satellite and mission requirements of user spacecraft,a static mission scheduling constraint model based on visible time window was established,which takes into account multiple visible time windows.On this basis,a static mission scheduling algorithm for relay satellite based on improved fireworks algorithm is proposed.Experimental results show that,compared with ant colony algorithm,the proposed algorithm can complete more scheduling missions and serve more high-priority tasks,which is suitable for practical application scenarios.