Joint Channel Characteristics in High-Speed Railway Multi-Link Propagation Scenarios: Measurement, Analysis, and Modeling

Zhou, Tao; Cheng, Tao; Salous, Sana; Liu, Liu

doi:10.1109/tits.2018.2868973

Cited by 18 publications

(9 citation statements)

References 32 publications

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“…(1) Propagation characteristics in the tube: For the design of wireless communications network, the knowledge of the wireless channel, which has a close relationship with propagation scenarios, is the fundamental basis. Different from traditional tunnel scenarios [21][22][23][24], which mainly consists of stone and clay, the vactrains are operating inside the fully enclosed metal tube wall, resulting in the unique propagation environment for wireless signal. From the aspect of waveguide, the concept of "mode" can be used to analyze the propagation characterization of radio waves in the tube [25,26].…”

Section: Key Challenges Of Vactrain's Wireless Communicationsmentioning

confidence: 99%

Broadband Wireless Communication Systems for Vacuum Tube High-Speed Flying Train

et al. 2020

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A vactrain (or vacuum tube high-speed flying train) is considered as a novel proposed rail transportation approach in the ultra-high-speed scenario. The maglev train can run with low mechanical friction, low air resistance, and low noise mode at a speed exceeding 1000 km/h inside the vacuum tube regardless of weather conditions. Currently, there is no research on train-to-ground wireless communication system for vactrain. In this paper, we first summarize a list of the unique challenges and opportunities associated with the wireless communication for vactrain, then analyze the bandwidth and Quality of Service (QoS) requirements of vactrain’s train-to-ground communication services quantitatively. To address these challenges and utilize the unique opportunities, a leaky waveguide solution with simple architecture but excellent performance is proposed for wireless coverage for vactrains. The simulation of the leaky waveguide is conducted, and the results show the uniform phase distribution along the horizontal direction of the tube, but also the smooth field distribution at the point far away from the leaky waveguide, which can suppress Doppler frequency shift, indicating that the time-varying frequency-selective fading channel could be approximated as a stationary channel. Furthermore, the train-to-ground wireless access architectures based on leaky waveguide are studied and analyzed. Finally, the moving scheme is adopted based on centralized, cooperative, cloud Radio Access Network (C-RAN), so as to deal with the extremely frequent handoff issue.

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Section: Key Challenges Of Vactrain's Wireless Communicationsmentioning

confidence: 99%

Broadband Wireless Communication Systems for Vacuum Tube High-Speed Flying Train

et al. 2020

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“…Assisted by the LTE networks on HSR, the multi-link cross-correlations were measured and analyzed, and the correlation matrix collinearity and sum rate capacity of dual-link HSR MIMO channels were evaluated in [28]. A model of joint statistical characteristics for HSR multi-link channels has been proposed in [29]. In addition, the Markov chain was used to statistically model the dynamic behavior of multipath components in time domain in HSR scenarios [30].…”

Section: A Statistical Channel Modelingmentioning

confidence: 99%

Channel Modeling for Future High-Speed Railway Communication Systems: A Survey

Zhou

Wang

et al. 2019

IEEE Access

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The widespread popularity of high-speed railways (HSRs) urges a critical demand on highdata-rate railway communication services for both train operation and passenger experience. To satisfy the ever-increasing requirements, future HSR communication systems, such as long-term evolution for railway (LTE-R), fifth generation (5G) on HSR, and 5G for railway (5G-R), and corresponding transmission technologies, e.g., mobile relay, coordinated multipoint, massive multiple-input multiple-output (MIMO), and millimeter-wave (mmWave), have recently attracted much attention. Radio channel modeling is the foundation of design and evaluation of wireless systems and transmission technologies. This paper focuses on a survey of channel modeling for the future HSR communication systems. The significant requirements of future HSR channel models are highlighted, and recent advances in the HSR channel modeling are reviewed. Finally, potential research directions for future HSR channel modeling are outlined.INDEX TERMS 5G, high-speed railway communications, channel modeling, multi-link, massive MIMO, millimeter-wave, nonstationarity, clustering, and deep learning.

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“…subway [19], viaduct [20], tunnel [19,21], HSR open area [15]; for special applications in HSR, e.g. optimising the arrangement of base stations to reduce the cost [22], cell coverage determination [23], joint channel characteristics in cooperative multi-link systems [24]. For context detection, the most common method relies on the global positioning system (GPS).…”

Section: Related Workmentioning

confidence: 99%

Random forests‐enabled context detections for long‐term evolution network forrailway

Zhang

et al. 2019

IET Microwaves, Antennas & Propagation

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An ensemble learning‐based approach for context detection for high‐speed railway (HSR) isproposed, evaluated, and compared against various machine learning algorithms.The context information is collected and formatted from the realistic physicaldata, which are measured by the field test in a commercial 4G cellular networkon‐board high‐speed train in an open area, HSR station, and typical urban area.The radio propagation knowledge implies that the channel model is implemented infeature extractions. The independent out‐of‐bag errors show ensemble learningapproaches; especially, random forests‐based algorithm achieves very accuratecontext detection (up to 93.5%), which is much higher than single tree (66%).Other ensembles with sub‐spaces of discriminant (67%) and K‐nearest neighbour(69%), as well as linear discriminant analysis (55.7%), and support vectormachine (SVM) (27.7%). Furthermore, the features are selected based on thefeature importance evaluation in the first round training. The selectedpredominant features and the reasonable number of individual trees construct therefined random forests, which obtain a high accuracy (92.6%) and 70% timereducing. This experimental study benefits from physical radio knowledge tosupport advanced long‐term evolution (LTE) network for railway and future smartrail applications.

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Joint Channel Characteristics in High-Speed Railway Multi-Link Propagation Scenarios: Measurement, Analysis, and Modeling

Cited by 18 publications

References 32 publications

Broadband Wireless Communication Systems for Vacuum Tube High-Speed Flying Train

Broadband Wireless Communication Systems for Vacuum Tube High-Speed Flying Train

Channel Modeling for Future High-Speed Railway Communication Systems: A Survey

Random forests‐enabled context detections for long‐term evolution network forrailway

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