Time-varying Contact Management with Dynamic Programming for LEO Satellite Networks

Abstract

The LEO satellite network (LSN) is envisioned to be highly advanced and ubiquitous, as a function complement and enhancement of ground networks. The satellite networking enables low-latency and high-speed data transmission over long distances for global users, especially in remote areas. Since the nature of time-variability, it is not easy to arrange the satellite networking scheme for tasks at each time slot. Specifically, the main problem is how to ensure that the networking scheme always follows the maximum network transmission capacity during the task duration. To address the problem, this paper first constructs a time-varying LSN model to describe the network characteristics. The networking problem is formulated as the maximum network transmission capacity (NTC) problem at each time slot. Next, a two-stage contact optimization scheme is given. The transmission-based depth first search (TDFS) algorithm is first proposed to calculate the optimal networking for each specified time slot. Then a network performance graph (NPG) is constructed to show the NTC performances of different time slot combinations. The dynamic programming is utilized on NPG to find the optimal time slot sequence. Simulation results show that the proposed contact management with dynamic programming (CMDP) scheme achieves better network throughput and service continuity for LSN.