An adaptive hidden Markov model for indoor OFDM based wireless systems

Abstract

Detailed physical layer simulation of orthogonal frequency division multiplexing (OFDM) systems requires programs that execute too slowly due to long coherence time of the indoor mobile channel. Evaluation of higher layers of such systems is simplified if suitable models for reproduction of channel errors statistics are available. An adaptive hidden Markov model (HMM) for indoor OFDM based systems that accurately reproduces error statistics of the real system with less computational effort than the exact simulation is presented in this paper. The standard HMM methodology has been modified in order to reproduce the periodicity in the error positions of the OFDM systems. The proposed model is validated by comparison of three statistical parameters: number of errors, length of the errors run and length of the error-free intervals in a frame of bits.