{'fraction_non_alphanumeric': 0.015151515151515152, 'fraction_numerical': 0.006060606060606061, 'mean_word_length': 5.355769230769231, '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}}
Modulation classification of PSK signals in multipath and frequency offsets

In this paper, we propose and evaluate a feature-based hierarchical modulation classification algorithm to perform classification in presence of multipath channels and frequency offsets. We use a combination of features based on second-order cyclic autocorrelation function and moments-based statistics. The proposed approach does not require a priori information regarding the multipath channel, or the pulse shape used at the transmitter. The proposed algorithm achieves very good results for the COST-207 channel models in the presence of frequency offsets even at an SNR of 2 dB.