Coordinated Planning Transmission Tasks in Heterogeneous Space Networks:A Semi-Distributed Approach

This paper studies the coordinated planning of transmission tasks in the heterogeneous space networks to enable efficient sharing of ground stations cross satellite systems.Specifically,we first formulate the coordinated planning problem into a mixed integer liner programming(MILP)problem based on time expanded graph.Then,the problem is transferred and reformulated into a consensus optimization framework which can be solved by satellite systems parallelly.With alternating direction method of multipliers(ADMM),a semi-distributed coordinated transmission task planning algorithm is proposed,in which each satellite system plans its own tasks based on local information and limited communication with the coordination center.Simulation results demonstrate that compared with the centralized and fully-distributed methods,the proposed semi-distributed coordinated method can strike a better balance among task complete rate,complexity,and the amount of information required to be exchanged.

Learning to Optimize for Resource Allocation in LTE-U Networks

This paper proposes a deep learning(DL)resource allocation framework to achieve the harmonious coexistence between the transceiver pairs(TPs)and the Wi-Fi users in LTE-U networks.The nonconvex resource allocation is considered as a constrained learning problem and the deep neural network(DNN)is employed to approximate the optimal resource allocation decisions through unsupervised manner.A parallel DNN framework is proposed to deal with the two optimization variables in this problem,where one is the licensed power allocation unit and the other is the unlicensed time fraction occupied unit.Besides,to guarantee the feasibility of the proposed algorithm,the Lagrange dual method is used to relax the constraints into the DNN training process.Then,the dual variable and the DNN parameter are alternating update via the batch-based gradient decent method until the training process converges.Numerical results show that the proposed algorithm is feasible and has better performance than other general algorithms.

Utilization and Analysis of Resource Mobility in Space Information Networks

In space information networks,resource mobility is an important factor affecting the network performance,which not only results in challenges in resource management but also brings opportunities to the improvement of network service capability.In order to explore the restriction and improvement mechanism of resource mobility on network performance,we firstly use the time-expanded resource relationship graph to represent the moving behavior of multidimensional resources and the collaborative relationship between different resources.Then by jointly considering the number of disjoint resource combinations,the length of moving time window,and the parameter of resource independence,we propose(k,n,L)degree of freedom on resource combination as a metric measuring performance gain resulted from resource mobility.Furthermore,the analysis of resource mobility is transformed into the problem of finding disjoint paths in the graph,and the tradeoff relationship between QoS requirements of task and resource mobility utilization is discussed.Finally,the tradeoff between the gain of resource mobility utilization and the payment of service process delay is revealed through simulation.

Resource Mobility Aware Hybrid Task Planning in Space Information Networks

In this paper,a resource mobility aware two-stage hybrid task planning algorithm is proposed to reduce the resource conflict between emergency tasks and the common tasks,so as to improve the overall performance of space information networks.Specifically,in the common task planning stage,a resource fragment avoidance task planning algorithm is proposed,which reduces the contention between emergency tasks and the planned common tasks in the next stage by avoiding the generation of resource fragments.For emergency tasks,we design a metric to quantify the revenue of the candidate resource combination of emergency tasks,which considers both the priority of the tasks and the impact on the planned common tasks.Based on this,a resource mobility aware emergency task planning algorithm is proposed,which strikes a good balance between improving the sum priority and avoiding disturbing the planned common tasks.Finally,simulation results show that the proposed algorithm is superior to the existing algorithms in both the sum task priority and the task completion rate.