Markov Chain based models comparison 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 "1" and "0") 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 to identify the model that best describes the channel error behaviour in IEEE 802.16e.