{'fraction_non_alphanumeric': 0.014201183431952662, 'fraction_numerical': 0.0, 'mean_word_length': 5.409090909090909, '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}}
Maximum likelihood multichannel estimation under reduced rank constraint

This paper deals with the maximum likelihood estimation of the multichannel impulse response in a mobile communication system whose base stations are equipped with antennas arrays. The following problem is solved: using the training sequence, find the maximum likelihood multichannel impulse response from one mobile to the base station under a reduced rank constraint in the presence of Gaussian noise and jammers with unknown covariance matrix. Our results find applications in equalization (the reduced rank channel estimate can be used in a Viterbi algorithm), and in the estimation of the directions of arrival (DOA) of the paths from the mobile to the base station. In this last application, a MUSIC like algorithm is developed using the estimated channel subspace.