Cognitive Radio-Based Geostationary Satellite Communications for Ka-band Transmissions

This paper proposes an adaptive modulation scheme using rain fading predictions obtained via Kalman filtering in order to mitigate the effects of rain on cognitive radio-based geostationary (GEO) satellites operating in the Ka-band. In the proposed scheme, the need for adaptation is identified prior to the rain attenuation event, allowing for enough time for the transmitter and receiver to reconfigure, which is a requirement when one of the communicating nodes are moving at a certain relative speed. We show that the bit error rate (BER) performance can be improved by two orders of magnitude for a system that accounts for the overall delay when adapting its modulation scheme based on the proposed predictor outputs.