{'fraction_non_alphanumeric': 0.04284490145672665, 'fraction_numerical': 0.02056555269922879, 'mean_word_length': 5.488888888888889, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 1, '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}}
Correlation-Based Analytical Channel Modeling

Multiple-input multiple-output (MIMO) scheme is an important tool to achieve a high data rate communication and higher signal to noise ratio (SNR). In order to facilitate the communication system design, understanding and modeling the channel is crucial. Different approaches are available for modeling the MIMO channel based on the required utilization that range between physical and analytical approaches. In the case of analytical modeling, correlative-based modeling approach is common. Several papers illustrating this technique are available. In the case of ultra-wideband (UWB)-MIMO channel correlative modeling, few papers are available. This paper presents a brief elaboration on the correlative-based modeling, reviewing the most common available models and explains the practical way of implementing such modeling method. In addition, the case of modeling MIMOUWB channel is presented where proposed methods are explained. [Yasser Zahedi, Razali Ngah, Mastaneh Mokayef. MIMO Correlation-Based Analytical Channel Modeling. Life Sci J 2014;11(8s):558-562]. (ISSN:1097-8135). http://www.lifesciencesite.com. 116