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Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications...
In Earth-to-Space communications, well-known propagation effects such as path loss and atmospheric loss can lead to fluctuations in the strength of the communications link between a satellite and its ground station. Additionally, the typically unconsidered effect of shadowing due to the geometry of the satellite and its solar panels can also lead to link degradation. As a result of these anticipated...
This study defines a hardware architecture approach for software defined radios to enable commonality among NASA space missions. The architecture accommodates a range of reconfigurable processing technologies including general purpose processors, digital signal processors, field programmable date arrays (FPGAs), and application specific integrated circuits (ASICs) in addition to flexible and tunable...
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