Assessing the impact of real-time communication services on the space network ground segment

• Published in: 2016 IEEE Aerospace Conference pp. 1 - 13
• Main Authors: Sanchez Net, Marc, del Portillo, Inigo, Cameron, Bruce, Crawley, Edward
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-03-2016
• Subjects: Bandwidth; Earth; Real-time systems; Robots; Space communications; Space missions; Space vehicles
• DOI: 10.1109/AERO.2016.7500555

Communication networks to support space missions were originally architected around non-real time data services. In fact, missions have always required real-time services (e.g. telemetry and command), but the bulk of scientific data being returned to Earth has typically been highly delay tolerant. Nevertheless, future robotic and human exploration activities are rapidly pushing towards low latency, high data rate services. Examples can be found both in the near Earth domain (e.g. near real-imagery through NASAs LANCE program) and the deep space domain (e.g. HD video from Mars). Therefore, the goal of this paper is to quantify the effect of new real-time high data rate communication requirements on the ground segment of current communication networks. To that end, we start by analyzing operational schedules for NASAs Space Network (SN) in order to characterize the utilization of the overall network in terms of total data volume and contact time, as well as identify current mission drivers. These results are compared against proposed network requirements for future robotic and human near Earth exploration activities in order to quantitatively assess gaps in the SN capabilities. Using these results, we implement a rule-based expert system that translates SN-specific operational contacts into high-level data requirements for the ground segment of the network. We then exercise the expert system in order to derive the requirements that future exploration activities will impose on the SN. Finally quantify the impact of real-time data delivery services across NASAs ground segment by computing the wide-area network cost for different levels of data timeliness.