{'fraction_non_alphanumeric': 0.011461318051575931, 'fraction_numerical': 0.0, 'mean_word_length': 4.9743589743589745, '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}}
Adaptive crossed dipole antennas using a genetic algorithm

Antenna misalignment in a mobile wireless communications system results in a signal loss due to a decrease in antenna directivity and a polarization mismatch. A genetic algorithm (GA) is used to adaptively alter the polarization and directivity of a crossed dipole receive antenna in order to increase the link budget. The three orthogonal dipole configuration works better than only two crossed dipoles, but both improved the link loss as the angular pointing errors increased. A GA with a high mutation rate works best for a noiseless open loop adaptation, while a GA with a low mutation rate works best for noisy fully adaptive system.