Order estimation of HMM Discrete Channel Model for OFDM systems

OFDM systems popularly being used in current high data rate wireless access networks and international standards are practically implemented using FEC and interleaving schemes whose performance evaluation and analysis can greatly benefit from Discrete Channel Models developed for the underlying channel. In this paper the order i.e., minimum number of states required for the Hidden Markov discrete channel modelling of a typical OFDM system has been estimated by extensive simulation. The input sample period (T
s
) of the signal on which the channel acts, is seen to play a vital role in the HMMs for the OFDM systems. The models which have been completely derived for 4 different values of input sample period strongly indicate the need for specific evaluation of HMM channel models for different wireless standards. The Baum-Welch Algorithms (BWA) is used to train the HMM and to generate the HMM based error patterns which are compared with the original in terms of Autocorrelation functions and distribution probabilities of error intervals.