Abstract
Small satellite networks, with the advantage of remarkably less development cost and energy consumption with respect to geostationary relay platforms, are playing an increased role in nowadays earth observation. However, small satellites have limited transponders and energy budget, which makes it necessary to design efficient contact plans to improve the network throughput. This paper addresses such an issue of joint management of the energy and transponder resource to well match the mission demand and network resources. We adopt an extended time-evolving graph to characterize network resources and then, formulate the contact plan design problem with the goal of maximizing the throughput as a mixed-integer linear programming. Since the computational complexity of this problem coupling multiple time slots is prohibitive, we further propose two heuristic algorithms which operate on a slot-by-slot basis to achieve high throughput. Simulation results present the impact of different factors on the network performance and moreover, demonstrate that both our contact plan approaches can achieve high throughput with low complexity.
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