Low-Complexity Algorithm for Radio Astronomy Observation Data Transport in an Integrated NGSO Satellite Communication and Radio Astronomy System

Abstract

An integrated non-geostationary orbit (NGSO) satellite communication and radio astronomy system (SCRAS), was recently proposed in [1] as a new coexistence paradigm. In SCRAS, the transportation of the radio astronomical observation (RAO) data from the space to the ground stations is an important problem, for which [1] proposed a linear programming optimization based algorithm. However, the computational complexity of this algorithm is quite high which is exacerbated by the need to re-compute the algorithm frequently due to the time-varying characteristics of the observing satellites, the Earth stations, and the RAO region. In this paper, to address this high complexity issue, we develop a low-complexity RAO data transport algorithm. In addition to the static resource constraint scenario considered in the existing work, we introduce a dynamic resource constraint scenario to exploit the knowledge of the satellite communication system (SCS) traffic statistics. We also present a modified version of the algorithm in [1] for the dynamic resource constraint scenario. In addition to the number of inter-satellite link (ISL) hops as the RAO data transport cost metric, we also evaluate the metric of the sum of the squared ISL hop distances which reflects the transmission energy cost. Furthermore, computational complexity analysis and data transport costs of the algorithms are presented. Our results show that the proposed algorithm yields several orders of computational complexity saving over the existing method while incurring a modest increase in the data transport cost. Our proposed dynamic resource constraint scenario provides plausible reduction of the RAO data transport cost.

Keywords

• Clustering
• low-complexity
• non-geostationary orbit
• radio astronomy
• satellite communication