Efficient Range Segment Upgrade (ERSU) for Satellite Control Networks Using Stochastic Interference Prediction and Context-aware Smart Antenna Control
Abstract: A range segment upgrade for Air Force satellite control network (AFSCN) will significantly improve system effectiveness via spectrum sharing and seamless interoperation. However, the upgraded system requires new capabilities such as real-time and accurate RF interference detection and mitigation, array antenna backlobe/sidelobe suppressions, accurate performance degradation prediction, robust link power budget under uncertainty, etc. Accomplishing those goals is main keys enabling a range segment upgrade for AFSCN, however, the existing techniques provide only limited such capabilities. In this project, InfoBeyond and Oregon State University advocate an Efficient Range Segment Upgrade (ERSU) for AFSCN using stochastic interference prediction and context-aware smart antenna control to address these challenges. Firstly, ERSU provides a robust and accurate statistical interference estimation algorithm based on the tools of the Gaussian Markov Random Field. The proposed algorithm offers a real-time interference estimation given erroneous/corrupted spatial-temporal observations. Secondly, a hidden semi-Markov model based channel prediction algorithm is proposed for robust and accurate channel prediction. It is able to predict not only channel states but also the state duration. Finally, ERSU offers a context-aware stochastic decision making given the input uncertainties. The proposed scheme allows the transmitter efficient selects and controls array antenna enabling reliable multi-satellite receptions.