Point cloud-based environment reconstruction and ray tracing simulations for railway tunnel channels

Radio propagation environment plays a critical role in the performance of wireless communication systems,and understanding channel characteristics is vital for ensuring reliable communication links and optimizing system performance.Ray tracing is an effective method to investigate propagation characteristics in a complex environment,and how to quickly and accurately obtain environmental information needs to be solved.This paper presents dynamic environment reconstruction and ray tracing simulation in railway tunnel environment based on Simultaneous Localization and Mapping(SLAM)algorithm and Poisson reconstruction algorithm.Accurate channel parameters are obtained and analyzed based on ray tracing simulation.Both straight and curved tunnels are considered and investigated,and the results show the channel characteristics in complex railway tunnel environments.

MmWave extra-large-scale MIMO based active user detection and channel estimation for high-speed railway communications

The current High-Speed Railway(HSR)communications increasingly fail to satisfy the massive access services of numerous user equipment brought by the increasing number of people traveling by HSRs.To this end,this paper investigates millimeter-Wave(mmWave)extra-large scale(XL)-MIMO-based massive Internet-of-Things(loT)access in near-field HSR communications,and proposes a block simultaneous orthogonal matching pursuit(B-SOMP)-based Active User Detection(AUD)and Channel Estimation(CE)scheme by exploiting the spatial block sparsity of the XLMIMO-based massive access channels.Specifically,we first model the uplink mmWave XL-MIMO channels,which exhibit the near-field propagation characteristics of electromagnetic signals and the spatial non-stationarity of mmWave XL-MIMO arrays.By exploiting the spatial block sparsity and common frequency-domain sparsity pattern of massive access channels,the joint AUD and CE problem can be then formulated as a Multiple Measurement Vectors Compressive Sensing(MIMV-CS)problem.Based on the designed sensing matrix,a B-SOMP algorithm is proposed to achieve joint AUD and CE.Finally,simulation results show that the proposed solution can obtain a better AUD and CE performance than the conventional CS-based scheme for massive IoT access in near-field HSR communications.

Attention Mechanism-Based Method for Intrusion Target Recognition in Railway

The detection of foreign object intrusion is crucial for ensuring the safety of railway operations.To address challenges such as low efficiency,suboptimal detection accuracy,and slow detection speed inherent in conventional comprehensive video monitoring systems for railways,a railway foreign object intrusion recognition and detection system is conceived and implemented using edge computing and deep learning technologies.In a bid to raise detection accuracy,the convolutional block attention module(CBAM),including spatial and channel attention modules,is seamlessly integrated into the YOLOv5 model,giving rise to the CBAM-YOLOv5 model.Furthermore,the distance intersection-over-union_non-maximum suppression(DIo U_NMS)algorithm is employed in lieu of the weighted nonmaximum suppression algorithm,resulting in improved detection performance for intrusive targets.To accelerate detection speed,the model undergoes pruning based on the batch normalization(BN)layer,and Tensor RT inference acceleration techniques are employed,culminating in the successful deployment of the algorithm on edge devices.The CBAM-YOLOv5 model exhibits a notable 2.1%enhancement in detection accuracy when evaluated on a selfconstructed railway dataset,achieving 95.0%for mean average precision(m AP).Furthermore,the inference speed on edge devices attains a commendable 15 frame/s.

Key technologies for wireless network digital twin towards smart railways

An emerging railway technology called smart railway promises to deliver higher transportation efficiency,enhanced comfort in services,and greater eco-friendliness.The smart railway is expected to integrate fifth-generation mobile communication(5G),Artificial Intelligence(AI),and other technologies,which poses new problems in the construction,operation and maintenance of railway wireless networks.Wireless Digital Twins(DTs),which have recently emerged as a new paradigm for the design of wireless networks,can address these problems and enable the whole lifecycle management of railway wireless networks.However,there are still many scientific issues and challenges for railway-oriented wireless DT.Relevant key technologies to solve these problems are introduced and described,including characterization of materials'physical-EM properties,autonomous reconstruction of Three-dimensional(3D)environment model,AI-empowered environmental cognition,Ray-Tracing(RT),model-based and AIbased RT acceleration,and generation of multi-spectra sensing data.Moreover,this paper presents our research results for each key technology and describes the wireless network planning and optimization system based on highperformance RT developed by our laboratory.This paper outlines the framework for realizing the wireless DT of smart railways,providing the direction for future research.

Stationarity Intervals of Time-Variant Channel in High Speed Railway Scenario

The non-stationary behavior, caused by the train rmverrent, is the rmin factor for the variation of high speed railway channel. To measure the tirce-variant effect, the parameter of stationarity interval, in which the channel keeps constant or has no great change, is adopted based on Zhengzfiou- Xi＇an （Zhengxi） passenger dedicated line measurement with different train speeds. The stationarity interval is calculated through the definition of Local Region of Stationarity （LRS） under three train ve- locities. Furthermore, the time non-stationary characteristic of high speed pared with five standard railway channel is corn- Multiple-Input MultipleOutput （MIMO） channel models, i.e. Spatial Channel Model （SCM）, extended version of SCM （SCME）, Wireless World Initiative New Radio Phase II （WINNERII）, International Mobile Teleconmnications-Advanced （IMT-Advanced） and WiMAX models which contain the high speed moving scenario. The stationarity interval of real channel is 9 ms in 80% of the cases, which is shorter than those of the standard models. Hence the real channel of high speed railway changes more rapidly. The stationarity intervals of standard models are different due to different modeling methods and scenario def- initions. And the compared results are instructive for wireless system design in high speed railway.

Finite-State Markov Wireless Channel Modeling for Railway Tunnel Environments

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.

High-speed railway channel measurements and characterizations: a review

Wireless communication for high-speed railways （HSRs） that provides reliable and high data rate communi- cation between the train and trackside networks is a challenging task. It is estimated that the wireless communication traffic could be as high as 65 Mbps per high-speed train. The development of such HSR communications systems and standards requires, in turn, accurate models for the HSR propagation channel. This article provides an overview of ex- isting HSR channel measurement campaigns in recent years. Particularly, some important measurement and modeling results in various HSR scenarios, such as viaduct and U-shaped groove （USG）, are briefly described and analyzed. In addition, we review a novel channel sounding method, which can highly improve the measurement efficiency in HSR environment.

Propagation characteristics of wideband high-speed railway channel in viaduct scenario at 2.35 GHz

In order to obtain accurate characteristics of wireless channels in the viaduct area of China, a channel meas- urement was taken in a railway viaduct scenario of the Zhengzhou-Xi＇an passenger dedicated line with a bandwidth of 50 MHz at 2.35 GHz. The single-slope log-distance model is used to analyze the path-loss （PL）, and the distribution of shadow fading （SF） is obtained by statistical methods, which shows that the normal distribution fits the samples well. Ricean K-factor is analyzed by the method of moments, and the variation of K-factor is given along the measured route. Small scale such as delay spread and Doppler behavior are parameterized. Based on empirical channel measurement, this paper provides parameters for the evaluation and simulation work on viaduct scenarios of high-speed railway.

A Novel Millimeter-Wave Channel Measurement Platform for 6G Intelligent Railway Scenarios

This paper presented a novel millimeterwave channel measurement platform for the 6G intelligent railway.This platform used phased array antenna with 64 elements and can support instant bandwidth up to 1 GHz.Combined with improved multi-tone sounding signals,the platform can enhance dynamic measurement capability in high-speed railway scenarios.We performed calibration works about frequency flatness,frequency offset and proved platform reliability with channel emulator based closed-loop verification.We also carried out field trials in high-speed railway carriage scenarios.Based on measurement results,we extracted channel characteristic parameters of path loss,power delay profile and delay spread to further verify the field measurement performance of the platform.

Investigation of Cross-Correlation Characteristics for Multi-Link Channels in High-Speed Railway Scenarios

This paper investigates the cross-correlation characteristics of large-scale parameters(LSPs) and small-scale fading(SSF) for high-speed railway(HSR) multilink propagation scenarios, based on realistic measurements conducted on Beijing to Tianjin HSR line in China. A long-term evolution-based channel sounding system is utilized in the measurements to obtain the channel data. By applying a proposed time-delay based dynamic partition method, multi-link channel impulse responses are extracted from the raw channel data. Then, the statistical results of LSPs, including shadow fading, K-factor, and root-mean-square delay spread are derived and the cross-correlation coefficients of these LPSs are calculated. Moreover, the SSF spatial correlation and cross-correlation of SSF are analyzed. These results can be used to exploit multi-link channel model and to optimize the next-generation HSR communication system.

Millimeter Wave and THz Propagation Channel Modeling for High-Data Rate Railway Connectivity--Status and Open Challenges

In the new era of railways, infrastructure, trains and travelers will be interconnected. In order to realize a seamless high-data rate wireless connectivity, up to dozens of GHz bandwidth is required. This motivates the exploration of the underutilized millimeter wave （mmWave） as well as the largely unexplored THz band. In this paper, we first identify relevant communication scenarios for railway applications. Then the specific challenges and estimates of the bandwidth requirements for high-data rate railway connec-tivity in these communication scenarios are described. Finally, we outline the major challenges on propagation channel modeling and provide a technical route for further studies.

Wireless Relay Communication on High Speed Railway：Full Duplex or Half Duplex？

In this paper,we introduce one full-duplex(FD) relaying transmission scheme for high speed railway and compare its ergodic capacity and outage performance with half-duplex(HD) relaying scheme. Both decode-and-forward(DF) amplify-and-forward(AF) relay modes are considered. Moreover,the carriage penetration loss(CPL) and the self-interference(SI) cancellation ratio are investigated. We derive the closed-form expressions for the outage probability and ergodic capacity of both HD and FD relay transmission schemes. It is shown that when CPL is larger than a certain level,the FD relay can achieve better performance in terms of capacity and keep the outage probability in a low level. It is also found that three factors: AF or DF modes,CPL and SI cancellation ratio,can have impact on capacity performance,and that CPL is one decisive factor. Our results can provide theoretical supports for development and deployment of future wireless communication systems on high speed railways.

Doppler frequency offset estimation and diversity reception scheme of high-speed railway with multiple antennas on separated carriage

The challenges of severe Doppler effects in high-speed railway are considered. By building a cooperative antenna system; an algorithm of joint channel estimation and Doppler frequency offset （DFO） estimation is proposed based on Ricean channel model. First, a maximum likelihood estimation （MLE） algorithm for DFO is designed, show- ing that the Doppler estimation can be obtained by estimating moving velocity of the train and the path loss with the exploitation of pilots that are placed inside the frame. Then a joint detection algorithm for the receiver is proposed to exploit multi-antenna diversity gains. Last, the theoretical Crammer Rao bound （CRB） for joint channel estimation and DFO estimation is derived. The steady performance of the system is confirmed by numerical simulations. In particular, when the Ricean fading channel parameter equals 5 and the velocities of train are 100 m/s and 150 m/s, the estimation variances of DFO are very close to the theoretical results obtained by using CRB. Meanwhile, the corresponding sig- nal to noise ratio loss is less than 1.5 dB when the bit error rate is 10-5 for 16QAM signals.

Railway switch fault diagnosis based on Multi-heads Channel Self Attention,Residual Connection and Deep CNN

A novel switch diagnosis method based on self-attention and residual deep convolutional neural networks(CNNs)is proposed.Because of the imbalanced dataset,the K-means synthetic minority oversampling technique(SMOTE)is applied to balancing the dataset at first.Then,the deep CNN is utilized to extract local features from long power curves,and the residual connection is performed to handle the performance degeneration.In the end,the multi-heads channel self attention focuses on those important local features.The ablation and comparison experiments are applied to verifying the effectiveness of the proposed methods.With the residual connection and multi-heads channel self attention,the proposed method has achieved an impressive accuracy of 99.83%.The t-SNE based visualizations for features of the middle layers enhance the trustworthiness.

Towards smart rail mobility at the mmWave and THz bands:Challenges, solutions, and future directions

In the vision of"smart rail mobility",a seamless high-data-rate wireless connectivity with up to dozens of GHz bandwidth will be required.This forms a strong motivation for exploring the underutilized millimeter wave(mmWave)and Terahertz(THz)bands.In this paper,we identify the main challenges and present the state-of-the-art solutions towards the realization of smart rail mobility.In order to cope with the challenge of involving the railway features in the channel models,we define and reconstruct the complete version and the concise version of the reference scenario modules for mmWave and THz railway channels.Simulations in the complete version of the scenarios reflect the influence of railway objects in detail;based on raytracing simulations in the concise version of the scenarios,two mmWave railway channel models are established and validated by measurements.Moreover,in order to tackle the challenge of heavy computing workload,we develop an open-access high performance ray-tracing platform—CloudRT.Last but not least,the challenges raised by the mmWave directional network under high mobility are overcome by our solutions concerning the handover scheme,random access procedure,and beamforming strategies.By integrating the key enabling technologies presented in this paper,we prototype the mobile hotspot network(MHN)system which realizes 1.25 Gbps downlink data throughput in a subway line with the train speed of 80 km/h.Future directions towards the full version of the smart rail mobility are pointed out as well.