Cognitive Anti-Jamming Satellite-To-Ground Communications on NASA's SCaN Testbed

[摘要] Machine learning aided cognitive anti-jamming communications is designed, developed and demonstrated on a live satellite-to-ground link. A wideband autonomous cognitive radio (WACR) is designed and implemented as a hardware-in-the- loop (HITL) prototype. The cognitive engine (CE) of the WACR is implemented on a PC while the software-defined radio (SDR) platform utilized two different radios for spectrum sensing and actual communications. The cognitive engine performs spectrum knowledge acquisition over the complete spectrum range available for the SATCOM system operation and learns an anti-jamming communications protocol to avoid both intentional jammers and inadvertent interferers using reinforcement learning. When the current satellite-to-ground link is jammed, the cognitive engine of the ground receiver directs the satellite transmitter to switch to a new channel that is predicted to be jammer-free for the longest possible duration. The end-to-end, closed-loop system was tested on the NASA Space Communications and Navigation (SCaN) Testbed on the International Space Station (ISS). The experimental results demonstrated the feasibility of satellite-to-ground cognitive anti-jamming communications along with excellent anti-jamming capability of machine learning aided cognitive protocols against several different types of jammers.

[发布日期] 2018-11-14

[学科分类] 航空航天科学

[关键词] COMMUNICATION NETWORKS;DATA LINKS;FEEDBACK CONTROL;GROUND STATIONS;JAMMING;MACHINE LEARNING;RADIO FREQUENCIES;SATELLITE COMMUNICATION;SATELLITE NAVIGATION SYSTEMS;SPECTRA;TEST STANDS;TRANSMITTERS;END-TO-END DATA SYSTEMS;RADIO EQUIPMENT