{'fraction_non_alphanumeric': 0.011235955056179775, 'fraction_numerical': 0.004213483146067416, 'mean_word_length': 5.79047619047619, '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}}
Partial Sparse Channel Estimation Based on Optimal SL0 Algorithm

Abstract In this paper we establish the partial sparse channel and make the channel estimation by optimal SL0 algorithm. In the channel estimation, derive the theoretical model of compressed sensing and verify the feasibility of channel estimation algorithm. The model can reconstruct the original signal more accurately and suppress the interference more effectively. The simulation and analytical results show that optimal SL0 algorithm is better than other algorithms in MSE, reconstruction precision, matching degree of signal and the compute complexity, thereby validating the proposed algorithm and channel model in wireless communications.