Search Results (29)

To enable highly reliable and spectrum-efficient vehicle-to-everything (V2X) communications under conditions with severe Doppler effects and rapidly time-varying channels, we propose a novel faster-than-Nyquist orthogonal time frequency space (FTN-OTFS) modulation scheme. In this scheme, FTN signaling is integrated with spectrally efficient frequency division multiplexing (SEFDM) within the OTFS framework, enabling a higher symbol-transmission density within a fixed time–frequency resource block and thus enhancing spectral efficiency without increasing the occupied bandwidth. An analytical input–output model is derived in both the delay–Doppler and time–frequency domains. To further enhance numerical stability, an improved detection algorithm called adaptive damping log-domain message-passing (ADL-MP) is developed for the proposed scheme. Simulation results demonstrate that the proposed scheme achieves robust and reliable performance in high-mobility scenarios and that the proposed algorithm consistently outperforms conventional methods in terms of bit error rate (BER) under both the extended vehicular A (EVA) model and the high-speed train (HST) scenario, confirming its effectiveness and superiority for V2X communications. Full article

This paper presents a novel dual-band antenna design for simultaneous 5G communication and localization services in high-speed train (HST) scenarios. It operates in the frequency range 1 (FR1) n78 band at 3.5 GHz and the FR2 n258 band at 26.2 GHz. The design combines a dielectric resonator antenna (DRA) and a planar patch antenna to achieve dual-band functionality. This provides efficient performance across both mid-band and millimeter-wave frequencies for advanced 5G applications. The dual-band configuration is motivated by the need to balance wide coverage and high data rates within a single, compact antenna design, addressing the specific challenges of maintaining stable connectivity and efficient spectrum utilization in high-speed, data-intensive environments. A common challenge in dual-band antenna designs is the interference between low- and high-frequency antennas, which can significantly degrade performance or even cause antenna failure. Our design addresses this issue by minimizing interference between the patch and DRA elements, ensuring stable operation across both frequency bands. As a result, the antenna achieves impressive gains and bandwidth, with a maximum gain of 6.8 dBi and an impedance bandwidth of 22.5% for the dual-band configuration. Also, both radiators present high total efficiency above 90%. The compact size of the antenna makes it highly suitable to be mounted on the roof of the train to enable 5G communication and location-based services for both safety-critical and liability-critical applications in HST scenarios. Full article

In this paper, the idea of a radar based on orthogonal frequency division multiplexing (OFDM) is applied to 5G NR Positioning Reference Signals (PRS). This study demonstrates how the estimation of the communication channel using the PRS can be applied for the identification of objects moving near the 5G NR receiver. In this context, this refers to a 5G NR base station capable of detecting a high-speed train (HST). The anatomy of a 5G NR frame as a sequence of OFDM symbols is presented, and different PRS configurations are described. It is shown that spectral analysis of time-varying channel impulse response weights, estimated with the help of PRS pilots, can be used for the detection of transmitted signal reflections from moving vehicles and the calculation of their time and frequency/Doppler shifts. Different PRS configurations with varying time and frequency reference signal densities are tested in simulations. The peak-to-noise-floor ratio (PNFR) of the calculated radar range–velocity maps (RVM) is used for quantitative comparison of PRS-based radar scenarios. Additionally, different echo signal strengths are simulated while also checking various observation window lengths (FFT lengths). This study proves the practicality of using PRS pilots in remote sensing; however, it shows that the most dense configurations do not provide notable improvements, while also demanding considerably more resources. Full article

To enhance the operational efficiency of high-speed trains (HSTs), Train-to-Train (T2T) communication has received considerable attention. This paper introduces a T2T cooperative communication model that allows direct information exchange between HSTs, enhancing communication efficiency and system performance. The model incorporates a mix of dynamic and static nodes, and within this framework, we have developed a novel Dynamic Hierarchical Algorithm (DHA) to optimize communication paths. The DHA combines the stability of traditional algorithms with the flexibility of machine learning to adapt to changing network topologies. Furthermore, a communication link quality assessment function is proposed based on stochastic network calculus, which accounts for channel randomness, allowing for a more precise adaptation to the actual channel environment. Simulation results demonstrate that DHA has superior performance in terms of optimization time and effect, particularly in large-scale and highly dynamic network environments. The algorithm’s effectiveness is validated through comparative analysis with traditional and machine learning-based approaches, showing significant improvements in optimization efficiency as the network size and dynamics increase. Full article

Railway traction motor bearings (RTMB) are critical components in high-speed trains (HST) that are particularly susceptible to failure due to the high stress and rotational frequency they experience. To address the challenge of high false-positive rates in existing monitoring systems, this paper introduces a novel sensorless monitoring scheme that leverages stator current to detect fault-related characteristics, eliminating the need for additional sensors. This approach employs a hybrid signal preprocessing algorithm that integrates adaptive notch filtering (ANF) with envelope spectrum analysis (ESA) to effectively sparse the stator current and extract relevant fault features. A deep belief network (DBN) is utilized for the classification of the health status of the RTMB. To validate the scheme’s feasibility and effectiveness, we conducted experiments on a 1:1 scale high-speed railway traction motor, demonstrating that mechanical defects in RTMB can be reliably indicated by changes in stator current. Based on the analysis of experimental results, it was concluded that the fault detection accuracy of RTMB based on stator current is at least 17.3% higher than that of the fault diagnosis methods based on vibration in diagnosing whether the system has a fault. Among them, the method proposed in this paper is the best in diagnosing the presence and type of faults, with an accuracy that is at least 8.9% higher than other methods. This study not only presents a new method for RTMB monitoring but also contributes to the field by offering a more accurate and efficient alternative to current practices. Full article

When high-speed trains (HSTs) rapidly enter or exit the wind barrier area of the bridge, the quick change in the operating environment can lead to sudden changes in train aerodynamic loads, resulting in the deterioration of their aerodynamic performance and adversely affecting safe and stable operation. In this paper, the effects of wind barrier porosity, crosswind speed, and train speed on the sudden change in the aerodynamic load of the HST induced by wind barriers are analyzed, and the reasons for the sudden change from a flow field perspective are given. Additionally, the influences of the buffer structure with three lengths of 45 m, 90 m, and 135 m on the sudden change in the aerodynamic load of HSTs are studied. The results show that the lower the porosity of the wind barrier, the higher the crosswind speed, and the lower the speed of trains entering and exiting the wind barrier area, resulting in a greater degree of sudden change in the aerodynamic load of the HST. The buffer structure measuring 90 m in length is considered the most suitable, as it can significantly alleviate the sudden change in the aerodynamic load and effectively enhance the safety of train operations. Full article

The Doppler effect caused by the rapid movement of high-speed rail services has a great impact on the accuracy of train positioning and speed measurement. Existing train positioning algorithms require a large number of trackside equipment and sensors, resulting in high construction and maintenance costs. Aiming to solve the above two problems, this article proposes a train positioning algorithm based on orthogonal time–frequency space (OTFS) modulation and integrated sensing and communication (ISAC). Firstly, based on the OTFS, the positioning and speed measurement architecture of communication awareness integration is constructed. Secondly, a two-stage estimation (TSE) algorithm is proposed to estimate the delay Doppler parameters of HST. In the first stage, a low-complexity coarse grid search is used, and in the second stage, a refined off-grid search is used to obtain the delay Doppler parameters. Then, the time difference of arrival/frequency difference of arrival (TDOA/FDOA) algorithm based on multiple base stations is used to locate the target, the weighted least square method is used to calculate the location, and the Cramér–Rao lower bound (CRLB) for positioning and speed measurement is derived. The simulation results demonstrate that, compared to GNSS/INS and OFDM radars, the algorithm exhibits enhanced positioning and speed measurement accuracy. Full article

Traditional bearing fault diagnosis methods struggle to effectively extract distinctive, domain-invariable characterizations from one-dimensional vibration signals of high-speed train (HST) bearings under variable load conditions. A deep migration fault diagnosis method based on the combination of a domain-adversarial network and signal reconstruction unit (CRU) is proposed for this purpose. The feature extraction module, which includes a one-dimensional convolutional (Cov1d) layer, a normalization layer, a ReLU activation function, and a max-pooling layer, is integrated with the CRU to form a feature extractor capable of learning key fault-related features. Additionally, the fault identification module and domain discrimination module utilize a combination of fully connected layers and dropout to reduce model parameters and mitigate the risk of overfitting. It is experimentally validated on two sets of bearing datasets, and the results show that the performance of the proposed method is better than other diagnostic methods under cross-load conditions, and it can be used as an effective cross-load bearing fault diagnosis method. Full article

Smart cities like Neom require efficient and reliable transportation systems to support their vision of sustainable and interconnected urban environments. High-speed trains (HSTs) play a crucial role in connecting different areas of the city and facilitating seamless mobility. However, to ensure uninterrupted communication along the rail lines, advanced communication systems are essential to expand the coverage range of each base station (BS) while reducing the handover frequency. This paper presents the dual transceiver free space optical (FSO) communication system as a solution to achieve these objectives in the operational environment of HSTs in Neom city. Our channel model incorporates log-normal (LN) and gamma–gamma (GG) distributions to represent channel impairments and atmospheric turbulence in the city. Furthermore, we integrated the siding loop model, providing valuable insights into the system in real-world scenarios. To assess the system’s performance, we formulated the received signal-to-noise ratio (SNR) of the network under assumed fading conditions. Additionally, we analyzed the system’s bit error rate (BER) analytically and through Monte Carlo simulation. A comparative analysis with reconfigurable intelligent surfaces (RIS) and relay-assisted FSO communications shows the superior coverage area and efficiency of the dual transceiver model. A significant reduction of up to 76% and 99% in the number of required BSs compared to RIS and relay, respectively, is observed. This reduction leads to fewer handovers and lower capital expenditure (CAPEX) costs. Full article

High-speed railway (HSR) lines commonly operate over hundreds of kilometers, crossing several other large-scale infrastructures, such as highways, tunnels, bridges, and pipelines. This fact makes adjacent infrastructure more vulnerable to high-speed train (HST)-induced vibrations; thus, their potential distress should be carefully examined. The current study aims to assess the level of traffic-induced vibrations on the surface of buried pipelines vertically crossing under an HSR line. Firstly, the necessity to reduce high vibration levels is highlighted, utilizing a three-dimensional (3D) finite element model in conjunction with the moving load approach. Subsequently, an efficient mitigation measure is proposed to minimize these vibrations. For this purpose, a low-weight, high-performance geosynthetic fill material, i.e., expanded polystyrene (EPS) geofoam blocks, has been implemented between the HSR line and the buried pipeline to minimize the impact of vibrations. In this manner, HST-induced vibrations are reflected on EPS blocks, preventing them from reaching the pipeline surface. Based on this detailed parametric study, useful conclusions are drawn regarding the mechanical properties and geometry of the EPS protection layer. Full article

This study focuses on the stiffness and dynamic characteristic rules of a bridge approach zone in a high-speed railway (HSR). Indoor and in situ tests were performed to explore the stiffness and dynamic characteristics of the roadbed filling. Based on the test results, an effective track-subgrade finite element model (FEM) of a high-speed train (HST) was established. The FEM simulated the train load and model boundaries based on the obtained loads and viscoelastic artificial boundaries. Suitable elements were then selected to simulate the various components of the system and the constraint equations were established and solved using multi-point constraints. The model was verified by comparing the time–history curve characteristics, the frequency-domain characteristics and the results obtained from different modeling methods with the measured results. The influence of stiffness on the dynamic characteristics of the bridge approach zone were subsequently analyzed based on the aforementioned tests and simulations. The results indicate that (i) the model produced reliable results using the proposed approach; (ii) the influence of train load on the embankment was generally reflected in the upper part of the structure, and thus, bed structures are recommended to be strengthened; and (iii) under stationarity, the stiffness ratio between the bridge and normal subgrade is recommended as 1:6, with a transition length of 25 m. Full article

In recent years, the use of massive multiple-input multiple-output (MIMO) systems and higher frequency bands for next-generation urban rail transportation systems has emerged as an intriguing research topic due to its potential to significantly increase network capacity by utilizing available narrowband and broadband spectrums. In metro and mining applications, the high-reliability wireless sensor network (WSN) plays a vital role in providing personal safety, channel optimization, and improving operational performance. Through the duration of 1921–2023, this paper provides the survey on the progress of fifth-generation (5G) and beyond-fifth-generation (B5G) wireless communication systems in underground environments such as tunnels and mines, the evolution of the earliest technologies, development in channel modeling for vehicle-to-vehicle (V2V) communications, and realization of different wireless propagation channels in high-speed train (HST) environments. In addition, the most recent advanced channel modeling methods are examined, including the development of new algorithms and their use in intelligent transportation systems (ITS); mathematical, analytical, and experimental techniques for propagation design; and the significance of the radiation characteristics, antenna placing, and physical environment effect on wireless communications. Leaky coaxial cable (LCX) and distributed antenna system (DAS) designs are introduced in the demonstrated systems for improving the channel capacity of narrowband and wideband channels as well as the spatial characteristics of various MIMO systems. The review article concludes by figuring out open research directions for future technologies. Full article

With the increase in high-speed train (HST) operation speed, the light-weight design of the train body and component structure is pursued to reduce energy consumption during operation, but this seriously deteriorates the aerodynamic performance of the light-weight structure outside the train body under the effect of strong unsteady airflow, and the more obvious case is the frequently occurring problem of vibration, large deformation, and damage to the rubber exterior windshield at the connection position of HST carriages. We investigate the fluid–structure coupling mechanism of the interaction between the rubber external windshield and aerodynamic force, and compare the dynamic characteristics of windshield structure under different design parameters. A numerical simulation of three rubber outer windshield structure parameters (sidewall distance of U-shaped capsule, sidewall thickness, sidewall inclination angle) is carried out using FSI simulation of the two-way coupling method. The aerodynamic load, airflow dynamics around the windshield, and the nonlinear vibration and deformation form of the windshield is analyzed in detail. The results show that the aerodynamic response of the HST rubber external windshield analyzed by the FSI method is in good agreement with the full-scale test results. Additionally, the stiffness of the windshield can be improved by increasing the thickness of the windshield sidewall. When the distance between the sidewall of the windshield is increased, an insufficient thickness at the top of the arc causes a large local deformation at the top of the arc of the windshield. The method established and relevant research results can provide good support for the aerodynamic stability evaluation of HST windshields. Full article

During channel modeling for high-mobility channels, such as high-speed train (HST) channels, the velocity of the mobile radio station is assumed to be constant. However, this might not be realistic due to the dynamic movement of the train along the track. Therefore, in this paper, an enhanced Gauss–Markov mobility model with a 3D non-stationary geometry based stochastic model (GBSM) for HST in MIMO Wireless Channels is proposed. The non-isotropic scatterers within a cluster are assumed to be around the sphere in which the mobile relay station (MRS) is located. The multi-path components (MPCs) are modeled with varying velocities, whereas the mobility model is a function of time. The MPCs are represented in a death–birth cluster using the Markov process. Furthermore, the channel statistics, i.e., the space-time correlation function, the root-mean-square Doppler shift, and the quasi-stationary interval, are derived from the non-stationary model. The model shows how the quasi-stationary time increases from 0.21 to 0.451 s with a decreasing acceleration of 0.6 to 0.2 m/s${}^2$ of the HST. In addition, the impact of the distribution of the angles on the channel statistics is presented. Finally, the simulated results are compared with the measured results. Therefore, there is a close relationship between the proposed model and the measured results, and the model can be used to characterize the channel’s properties. Full article

The high-speed train (HST) is one of the most important transport tools in China, and the sound quality of its interior noise affects passengers’ comfort. This paper proposes a HST sound quality model. The model combines Mel-scale frequency cepstral coefficients (MFCCs), the most popular spectral-based input parameter in deep learning models, with convolutional neural networks (CNNs) to evaluate the sound quality of HSTs. Meanwhile, two input channels are applied to simulate binaural hearing so that the different sound signals can be processed separately. The binaural MFCC-CNN model achieves an accuracy of 96.2% and outperforms the traditional shallow neural network model because it considers the time-varying characteristics of noise. The MFCC features are capable of capturing the characteristics of noise and improving the accuracy of sound quality evaluations. Besides, the results suggest that the time and level differences in sound signals are important factors affecting sound quality at low annoyance levels. The proposed model is expected to optimize the comfort of the interior acoustic environment of HSTs. Full article