Link adaptation of MIMO-OFDM systems using hidden Markov model for high speed railway

Abstract

A link adaptation scheme for MIMO-OFDM systems over high speed rail environment is addressed in this paper. In this study, a selection method of MIMO transmission mode and the modulation and coding scheme (MCS) according to the Rician channel K-factor from our previous work is considered. A hidden Markov model of time-varying Rician channel K-factor is constructed by using the real measured channel data on the high speed rail train. With the constructed hidden Markov model, the time correlation of Rician channel K-factor can be obtained and the time-varying K-factor value can be generated. By using the hidden Markov model, the K-factor value can be predicted to facilitate link adaptation since the K-factor may vary during feedback, especially in high mobility scenario. Simulation results show an average throughput improvement of 5Mbps.