High-speed Train Channel Research Articles

The Effect of High-Speed Train Channel on the Performance of DVB-Terrestrial Communication Systems

The Effect of High-Speed Train Channel on the Performance of DVB-Terrestrial Communication Systems

Non-Stationarity Characterization and Geometry-Cluster-Based Stochastic Model for High-Speed Train Radio Channels

In time-variant high-speed train (HST) radio channels, the scattering environment changes rapidly with the movement of terminals, leading to a serious deterioration in communication quality. In the system-and link-level simulation of HST channels, this non-stationarity should be characterized and modeled properly. In this paper, the sizes of the quasi-stationary regions are quantified to measure the significant changes in channel statistics, namely, the average power delay profile (APDP) and correlation matrix distance (CMD), based on a measurement campaign conducted at 2.4 GHz. Furthermore, parameters of the multi-path components (MPCs) are estimated and a novel clustering-tracking-identifying algorithm is designed to separate MPCs into line-of-sight (LOS), periodic reflecting clusters (PRCs) from power supply pillars along the railway, and random scattering clusters (RSCs). Then, a non-stationary geometry-cluster-based stochastic model is proposed for viaduct and hilly terrain scenarios. Furthermore, the proposed model is verified by measured channel statistics such as the Rician K factor and the root mean square delay spread. The temporal autocorrelation function and the spatial cross-correlation function are presented. Quasi-stationary regions of the model are analyzed and compared with the measured data, the standardized IMT-Advanced (IMT-A) channel model, and a published non-stationary IMT-A channel model. The good agreement between the proposed model and the measured data demonstrates the ability of the model to characterize the non-stationary features of propagation environments in HST scenarios.

A Stochastic Confocal Elliptic-Cylinder Channel Model for 3D MIMO in Millimeter-Wave High-Speed Train Communication System

Massive MIMO technology is among the most promising solutions for achieving higher gain in 5G millimeter-wave (mmWave) channel models for high-speed train (HST) communication systems. Based on stochastic geometry methods, it is fundamental to accurately develop the associated MIMO channel model to access system performance. These MIMO channel models could be extended to massive MIMO with antenna arrays in more than one plane. In this paper, the proposed MIMO 3D geometry-based stochastic model (GBSM) is composed of the line of sight component (LOS), one sphere, and multiple confocal elliptic cylinders. By considering the proposed GBSM, the local channel statistical properties are derived and investigated. The impacts of the distance between the confocal points of the elliptic cylinder, mmWave frequencies of 28 GHz and 60 GHz, and non-stationarity on channel statistics are studied. Results show that the proposed 3D simulation model closely approximates the measured results in terms of stationary time. Consequently, findings show that the proposed 3D non-wide-sense stationary (WSS) model is better for describing mmWave HST channels in an open space environment.

Multidimensional Channel Characteristics Analysis in High‐Speed Train Scenarios

AbstractLTE for Railways (LTE‐R) is a next‐generation communication network dedicated to railway services, enabling high‐speed, reliable, and intelligent communications to ensure safety and efficiency for rail passengers. The wireless channel between the train and the ground is a key challenge in network design and optimization. The high‐speed train (HST) and its surrounding scenarios bring nonstationarity and unique radio propagation characteristics to the HST channel. A comprehensive and in‐depth analysis of channel characteristics is the basis of channel modeling. In this paper, based on the measurement‐validation ray tracing (RT) simulator, the quasi‐stationary intervals are presented first to reasonably quantify channel statistical parameters. Next, the time‐varying multidimensional spectra of the channels in three typical HST scenarios are shown, including the power delay profile (PDP), the arrival/departure angular spectrum, and the Doppler spectrum. Moreover, the corresponding channel characteristic parameters are extracted, such as the root‐mean‐square (RMS) delay spread, angular spread, and Doppler spread. Based on multidimensional channel characteristic analysis, combined with multipath geometric parameters provided by RT, we extract significant scatterers and mine key physical factors that affect radio propagation in HST scenarios. This work lays a solid foundation for accurate time‐varying HST channel modeling.

Recent Developments and Future Challenges in Channel Measurements and Models for 5G and Beyond High-Speed Train Communication Systems

The fast developments of high-speed train (HST) and growing communication demands of users pose new challenges for HST communication systems. To provide reliable communication services, key 5G communication technologies, such as millimeter-wave (mmWave) and massive multiple-input multiple-output (MIMO), and potential architectures, such as coordinated multipoint and mobile relay station, are considered in future railway communications. New technologies and architectures will bring new channel propagation characteristics. Accurate channel models that can capture these channel characteristics play a critical role in the design and test of future railway communication systems. This article reviews the HST channel measurements conducted in different scenarios and frequency bands, and the advanced HST channel models. Then a novel HST channel model incorporating the mmWave and massive MIMO propagation characteristics is presented, and its frequency non-stationarity is analyzed. Finally, some future directions are discussed.

An Efficient MIMO Channel Model for LTE-R Network in High-Speed Train Environment

Long-term evolution for railway (LTE-R) represents a promising network for smart railway, enabling fast and reliable wireless communications on high-speed trains (HSTs) with speeds as high as 500 km/h. To the best of our knowledge, the existing channel models are insufficient to assess such performance. To fill this gap, we propose the tapped delay line model for a $2\times 2$ multiple-input multiple-output channel in typical LTE-R HST scenarios. The models are efficient, yet flexible, which can capture the essential channel characteristics in the delay domain, Doppler domain, and spatial domain. Due to the practical difficulties of HST channel measurements, the channel between the fixed transmitter and the high-mobile train cannot be recorded sufficiently for establishing these stochastic models. Therefore, we develop channel models using a ray-tracing (RT) simulator that is validated by HST channel measurements at 2.15 GHz. This paper gives a full parameterization for the proposed channel models, and presents their implementation in channel and link-level simulations. The verification is made through a comparison of the proposed models and the measurement-validated RT simulations in terms of the delay spreads, the eigenvalues, and the error vector magnitudes.

Towards Realistic High-Speed Train Channels at 5G Millimeter-Wave Band—Part I: Paradigm, Significance Analysis, and Scenario Reconstruction

The upcoming fifth-generation (5G) mobile communication system is expected to support high mobility up to 500 km/h, which is envisioned in particular for high-speed trains. Millimeter wave (mmWave) spectrum is considered as a key enabler for offering the “best experience” to highly mobile users. Despite that channel characterization is necessary for the mmWave system design and validation, it is still not feasible to directly do extensive mmWave mobile channel measurements on moving high-speed trains (HST) at a speed up to 500 km/h in the present. Thus, rather than conducting mmWave HST channel sounding directly with high mobility, this study proposes a viable paradigm for realizing the realistic HST channels at the 5G mmWave band. We first propose the whole paradigm. Then, we define the scenario of interest and select the main objects and materials. Afterwards, the electromagnetic and scattering parameters of the materials are measured and estimated between 26.5 GHz and 40 GHz. With this information, the most influential materials are determined through significance analysis. Correspondingly, we reconstruct the three-dimensional mmWave outdoor HST and tunnel scenario models. Through extensive ray-tracing simulations, we determine the main propagation mechanisms in these two scenarios, the channel models based on that are validated by measurements. This verifies the whole paradigm proposed in this paper.

Towards Realistic High-Speed Train Channels at 5G Millimeter-Wave Band—Part II: Case Study for Paradigm Implementation

In this paper, we present two case studies for generating realistic high-speed train (HST) channels at fifth-generation (5G) millimeter-wave (mmWave) band. The first one is the tunnel environment at relatively low 5G mmWave band, 30 GHz band, whereas the second one is the outdoor HST environment at relatively high 5G mmWave band, 90 GHz band. Both case studies include the following steps: ray-tracing simulations, stochastic channel modeling and realization, verification with ray-tracing simulations, and validation with a reduced set of measurements. A profound and insightful conclusion is reached that by employing the proposed paradigm, realistic channels can be realized for the design and evaluation of 5G mmWave communication systems in high-speed railways, even without the support of sufficient channel sounding data.

A Geometry-Based Stochastic Channel Model for the Millimeter-Wave Band in a 3GPP High-Speed Train Scenario

This paper presents a geometry-based stochastic channel model (GSCM) for a 3GPP millimeter-wave (mmWave) high-speed train (HST) scenario. An important demand of the mmWave HST channel model is the spatial consistency during movement. In order to meet this requirement, the environment pattern containing the most effective geometry information is proposed, which is useful for generating an integral and accurate channel geometry. Since the measurement of a mmWave channel is deficient for high mobility, the proposed channel model is developed using a ray-tracing (RT) simulator that is validated with the channel measurements performed in the HST scenario at 93.2 GHz. The paper gives a full parameterization for the proposed model and its implementation for channel simulation. The verification is made through a comparison of the proposed model and the measurement-validated RT simulations in terms of the power delay profile, the Ricean $K$ -factor, and the second-order statistics for the delay and angle domains. Finally, for the design of mmWave HST communication systems, the time-varying channel characteristics are evaluated in the delay and Doppler domains.

Channel measurements and models for high-speed train wireless communication systems in tunnel scenarios: a survey

The rapid developments of high-speed trains (HSTs) introduce new challenges to HST wireless communication systems. Realistic HST channel models play a critical role in designing and evaluating HST communication systems. Due to the length limitation, bounding of tunnel itself, and waveguide effect, channel characteristics in tunnel scenarios are very different from those in other HST scenarios. Therefore, accurate tunnel channel models considering both large-scale and small-scale fading characteristics are essential for HST communication systems. Moreover, certain characteristics of tunnel channels have not been investigated sufficiently. This article provides a comprehensive review of the measurement campaigns in tunnels and presents some tunnel channel models using various modeling methods. Finally, future directions in HST tunnel channel measurements and modeling are discussed.

A Non-Stationary IMT-Advanced MIMO Channel Model for High-Mobility Wireless Communication Systems

With the recent developments of high-mobility wireless communication systems, e.g., high-speed train (HST) and vehicle-to-vehicle communication systems, the ability of conventional stationary channel models to mimic the underlying channel characteristics has widely been challenged. Measurements have demonstrated that the current standardized channel models, like IMT-Advanced (IMT-A) and WINNER II channel models, offer stationary intervals that are noticeably longer than those in measured HST channels. In this paper, we propose a non-stationary channel model with time-varying parameters, including the number of clusters, the powers, and the delays of the clusters, the angles of departure, and the angles of arrival. Based on the proposed non-stationary IMT-A channel model, important statistical properties, i.e., the local spatial cross-correlation function and local temporal autocorrelation function are derived and analyzed. Simulation results demonstrate that the statistical properties vary with time due to the non-stationarity of the proposed channel model. An excellent agreement is achieved between the stationary interval of the developed non-stationary IMT-A channel model and that of relevant HST measurement data, demonstrating the utility of the proposed channel model.

Channel measurements and models for high-speed train wireless communication systems in tunnel scenarios: a survey

The rapid developments of high-speed trains (HSTs) introduce new challenges to HST wireless communication systems. Realistic HST channel models play a critical role in designing and evaluating HST communication systems. Due to the length limitation, bounding of tunnel itself, and waveguide effect, channel characteristics in tunnel scenarios are very different from those in other HST scenarios. Therefore, accurate tunnel channel models considering both large-scale and small-scale fading characteristics are essential for HST communication systems. Moreover, certain characteristics of tunnel channels have not been investigated sufficiently. This article provides a comprehensive review of the measurement campaigns in tunnels and presents some tunnel channel models using various modeling methods. Finally, future directions in HST tunnel channel measurements and modeling are discussed.

A Simplified Multipath Component Modeling Approach for High-Speed Train Channel Based on Ray Tracing

High-speed train (HST) communications at millimeter-wave (mmWave) band have received a lot of attention due to their numerous high-data-rate applications enabling smart rail mobility. Accurate and effective channel models are always critical to the HST system design, assessment, and optimization. A distinctive feature of the mmWave HST channel is that it is rapidly time-varying. To depict this feature, a geometry-based multipath model is established for the dominant multipath behavior in delay and Doppler domains. Because of insufficient mmWave HST channel measurement with high mobility, the model is developed by a measurement-validated ray tracing (RT) simulator. Different from conventional models, the temporal evolution of dominant multipath behavior is characterized by its geometry factor that represents the geometrical relationship of the dominant multipath component (MPC) to HST environment. Actually, during each dominant multipath lifetime, its geometry factor is fixed. To statistically model the geometry factor and its lifetime, the dominant MPCs are extracted within each local wide-sense stationary (WSS) region and are tracked over different WSS regions to identify its “birth” and “death” regions. Then, complex attenuation of dominant MPC is jointly modeled by its delay and Doppler shift both which are derived from its geometry factor. Finally, the model implementation is verified by comparison between RT simulated and modeled delay and Doppler spreads.

Performance Investigation of Spatial Modulation Systems Under Non-Stationary Wideband High-Speed Train Channel Models

In this paper, the bit error rate (BER) performance of a new multiple-input-multiple-output technique, named spatial modulation (SM), is studied under a novel non-stationary wideband high-speed train (HST) channel model in different scenarios. Time-varying parameters obtained from measurement results are used to configure the channel model to make all results more realistic. A novel statistic property called the stationary interval in terms of the space-time correlation function is proposed to describe the channel model’s time-varying behavior. The accurate theoretical BER expression of SM systems is derived under the time-varying wideband HST channel model with the non-ideal channel estimation assumption. The simulation results demonstrate that the BER performance of SM systems shows a time-varying behavior due to the non-stationary property of the employed HST channel model. The system performance can maintain a relative stationary status within the specified stationary interval. It can also be observed that the BER performance of SM systems under the HST channel model is mainly affected by the correlation between sub-channels, inter-symbol-interference, Doppler shift, and channel estimation errors.

Channel Measurements and Models for High-Speed Train Communication Systems: A Survey

The recent development of high-speed trains (HSTs) as an emerging high mobility transportation system, and the growing demands of broadband services for HST users, introduce new challenges to wireless communication systems for HSTs. Accurate and efficient channel models considering both large-scale and non-stationary small-scale fading characteristics are crucial for the design, performance evaluation, and parameter optimization of HST wireless communication systems. However, the characteristics of the underlying HST channels have not yet been sufficiently investigated. This paper first provides a comprehensive review of the measurement campaigns conducted in different HST scenarios and then addresses the recent advances in HST channel models. Finally, key challenges of HST channel measurements and models are discussed and several research directions in this area are outlined.

Time-varying channel estimation through optimal piece-wise time-invariant approximation for high-speed train wireless communications

The practical time-varying channel between a high-speed train (HST) and infrastructure has a single Doppler shift on each resolvable multipath in most cases. As a result, the HST channel can be modelled by only 2L parameters: L Doppler shifts and L complex channel gains. Based on this observation, we propose a novel channel estimation technique for orthogonal frequency-division multiplexing (OFDM) systems running on a HST, with the name PIece-wise Time-Invariant Approximation (PITIA). In PITIA, the HST channel is approximated by a bunch of time-invariant channels, whose channel impulse responses (CIRs) can be estimated through pilots. Variations of these CIR samples over time derive both Doppler shifts and complex channel gains, so the whole time-varying channel can be reconstructed. PITIA enjoys low computation complexity of O(NL) for N subcarriers. The optimal duration of time-invariant channels used to approximate HST channel is derived from both analytical analysis and simulations. Compared to basis expansion model (BEM) methods, PITIA uses fewer channel parameters with comparable modelling error, shows better normalized mean squared error (NMSE) performance under high-mobility and high signal-to-noise ratio (SNR) environments, and achieves comparable NMSE in low SNR regime.