Joint allocation of transmission and computation resources for space networks

By allocating antenna time blocks to spacecrafts, data relay satellites are of vital importance for the space network to relay data within their visible intervals (i.e., time windows). Existing works concentrate only on the allocation of transmission resources (i.e., antenna time blocks) in time windows and may result in transmission conflicts hard to efficiently resolve, especially when multiple missions are activated simultaneously. To this end, we propose to further integrate computation with transmission resource allocation, to enable data compression so as to alleviate conflicts. Specifically, aiming to maximize the number of completed missions and minimize data loss, we first formulate the joint transmission and computation resource allocation problem as a mixed integer linear programming (MILP) one. Then, for the complexity reduction, we transform the MILP into an integer linear programming (ILP) one by fixing maximal data compression. Meanwhile, by constructing a conflict graph to characterize resource allocation conflicts, a time window scheduling algorithm is proposed to solve the ILP problem efficiently. Next, we further develop a data compression control algorithm to reduce data loss on the prerequisite of invariant mission number. Finally, simulation results show that the space network can benefit from the combination of transmission and computation resources in terms of both mission number and data loss.