{'fraction_non_alphanumeric': 0.019230769230769232, 'fraction_numerical': 0.0, 'mean_word_length': 5.451327433628318, '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}}
Link Evaluation for MIMO-OFDM System with ML Detection

Link evaluation is very important to system level simulation. Current algorithms for link evaluation show pretty good accuracy for wireless system with linear detections. However, when it comes to MIMO-OFDM system with ML Detection, problems still exists. This paper proposes an Extended Received Block Information Rate algorithm for link evaluation, which is deduced from the view of information and detecting theory. Accuracy and universality of this algorithm for MIMO-OFDM system with ML detection are highlighted. Simulation results show that, comparing to current algorithms for link evaluation, the proposed ERBIR algorithm obtains better accuracy and universality.