A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A non-stationary geometry-based stochastic model for MIMO high-speed train channels
In this paper, a non-stationary wideband geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) high-speed train (HST) channels. The proposed model employs multiple confocal ellipses model, where the received signal is a superposition of the line-of-sight (LoS) and single-bounced rays. Because of the time-varying feature of angles of arrival (AoAs), angles of departure (AoDs), and LoS angle, the proposed GBSM has the ability to investigate the non-stationarity of HST environment caused by the high speed movement of the receiver. From the proposed model, the local spatial cross-correlation function (CCF) and the local temporal autocorrelation (ACF) are derived for different taps. Numerical results and analysis show that the proposed channel model is capable of characterizing the time-variant HST wireless channel.
A non-stationary geometry-based stochastic model for MIMO high-speed train channels
In this paper, a non-stationary wideband geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) high-speed train (HST) channels. The proposed model employs multiple confocal ellipses model, where the received signal is a superposition of the line-of-sight (LoS) and single-bounced rays. Because of the time-varying feature of angles of arrival (AoAs), angles of departure (AoDs), and LoS angle, the proposed GBSM has the ability to investigate the non-stationarity of HST environment caused by the high speed movement of the receiver. From the proposed model, the local spatial cross-correlation function (CCF) and the local temporal autocorrelation (ACF) are derived for different taps. Numerical results and analysis show that the proposed channel model is capable of characterizing the time-variant HST wireless channel.
A non-stationary geometry-based stochastic model for MIMO high-speed train channels
Ghazal, A. (author) / Cheng-Xiang Wang, (author) / Haas, H. (author) / Beach, M. (author) / Mesleh, R. (author) / Dongfeng Yuan, (author) / Xiaohu Ge, (author) / Chahine, M. K. (author)
2012-11-01
3533686 byte
Conference paper
Electronic Resource
English
Time domain method for high speed train - bridge vertical stochastic vibration analysis
| British Library Online Contents | 2008
| Taylor & Francis Verlag | 2020
Prediction of high-speed train induced ground vibration based on train-track-ground system model
| Online Contents | 2010
Stochastic Seismic Responses of High-Speed Train–Bridge Systems with Ground Motion Correlation
| Springer Verlag | 2025