{'fraction_non_alphanumeric': 0.01726263871763255, 'fraction_numerical': 0.0, 'mean_word_length': 5.246153846153846, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
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.