Markov chain based models comparison and hybrid model design in IEEE 802.16E scenario

The IEEE 802.16e is a promising technology that allows to provide wireless broadband services to a great number of mobile users. Considering this interesting scenario enriched by further presence of HAPs (high altitude platform) with the role of base stations (BSs), we have proposed a comparison between performances of a set of Markov chain based models collected by literature. These following models: MTA (Markov-based trace analysis), Gilbert-Elliot, FSM (full-state Markov) and HMM (hidden Markov model) are designed using packet error traces (a sequence of ldquo1rdquo and ldquo0rdquo) obtained by a simulator that takes into account channel impairment effects such as path loss and Doppler effect. To compare the models performances, by each of them artificial traces are generated and then entropy normalized Kullback-Leibler distance, standard error and other statistical properties of random variable G (free error packets burst length) and B (corrupted packets burst length) of artificial traces are computed. The purpose of this work is not only to identify the model that best describes the channel error behaviour in IEEE 802.16e scenario but also to create a new one: after models comparison, a hybrid model designed to achieve excellent performance in the artificial traces generation will be presented.