摘要
In recent years,high-speed railways(HSRs)have developed rapidly with a high transportation capacity and high comfort level.A tunnel is a complex high-speed rail terrain environment.It is very important to establish an accurate channel propagation model for a railway tunnel environment to improve the safety of HSR operation.In this paper,a method for finite-state Markov chain(FSMC)channel modeling with least squares fitting based on non-uniform interval division is proposed.First,a path loss model is obtained according to measured data.The communication distance between the transmitter and receiver in the tunnel is non-uniformly divided into several large non-overlapping intervals based on the path loss model.Then,the Lloyd-Max quantization method is used to determine the threshold of the signal-to-noise ratio(SNR)and the channel state quantization value and obtain the FSMC state transition probability matrix.Simulation experiments show that the proposed wireless channel model has a low mean square error(MSE)and can accurately predict the received signal power in a railway tunnel environment.
In recent years, high-speed railways(HSRs) have developed rapidly with a high transportation capacity and high comfort level. A tunnel is a complex high-speed rail terrain environment. It is very important to establish an accurate channel propagation model for a railway tunnel environment to improve the safety of HSR operation. In this paper, a method for finite-state Markov chain(FSMC) channel modeling with least squares fitting based on non-uniform interval division is proposed. First, a path loss model is obtained according to measured data. The communication distance between the transmitter and receiver in the tunnel is non-uniformly divided into several large non-overlapping intervals based on the path loss model. Then, the Lloyd-Max quantization method is used to determine the threshold of the signal-to-noise ratio(SNR) and the channel state quantization value and obtain the FSMC state transition probability matrix. Simulation experiments show that the proposed wireless channel model has a low mean square error(MSE) and can accurately predict the received signal power in a railway tunnel environment.
基金
partially supported by Nation Science Foundation of China (61661025, 61661026)
Foundation of A hundred Youth Talents Training Program of Lanzhou Jiaotong University (152022)
