Modeling of radiowave propagation in tunnels

Boksiner, Jeffrey; Chrysanthou, Chrysanthos; Billah, Mashuk; Bocskor, Timothy; Barton, David K.; Breakall, James K.

doi:10.1109/milcom.2012.6415864

Cited by 5 publications

(12 citation statements)

References 9 publications

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“…Propagation in tunnels in which the tunnel shape is a periodic jointed tunnel was explained in [17]. Low-frequency propagation in idealistic rectangular-shaped tunnels was discussed in [1], [18], [19], and [20]. In [21], the propagation of radio waves was analyzed; the considered tunnels contained curved roads.…”

Section: A Geometric Shapes Of Tunnelmentioning

confidence: 99%

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Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

et al. 2023

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The prediction of radio signal transmission in tunnels is important for wireless communication link design as it enables the delivery of optimum power to the intended receiver inside the tunnel. Several techniques have been proposed to estimate path loss for wireless communication inside tunnels. The radio coverage range and where base stations need to be installed can be figured out with the help of propagation models. At the time of developing these models, modeling complexity and environmental attributes, such as the tunnel geometry and the electrical and magnetic properties of its walls and interior materials are considered. A limited amount of literature currently overviews how waves transmits through tunnels and how electromagnetic wave transmission has recently changed. This survey, which examines current advancements in the propagation of waves in tunnels, aims to address this gap. In this review, thirty wave propagation models were analyzed and grouped into distinct categories for the first time. The detailed specifications of each model were omitted to make the survey easy to comprehend. This comparative research will help service providers adopt an appropriate propagation model and plan efficient transmitter and receiver placement and link management for a specific tunnel environment.INDEX TERMS Artificial neural network, radio wave propagation, ray tracing, scaling, tunnel.

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Section: A Geometric Shapes Of Tunnelmentioning

confidence: 99%

“…In such instances, it is vital to know the features of the wireless channel at distances beyond the range of the usual tunnel base station. In contrast to wave propagation in an open space, electromagnetic wave propagation in tunnels uses modal decomposition and ray tracing mechanisms as the spaces are closed environments [1].…”

Section: Introductionmentioning

confidence: 99%

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

et al. 2023

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“…To date, several studies on communication channels have been conducted in various tunnels [6][7][8]. In contrast to open-air propagation, tunnel propagation includes electromagnetic waves in an enclosed environment [9]. A leaky feeder communication system can be deployed inside confined locations, in particular inside road or rail tunnels [5].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Modeling of Propagation in Tunnel at 3.7 and 28 GHz

Samad¹,

Choi²

2022

Computers, Materials &Amp; Continua

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In present-day society, train tunnels are extensively used as a means of transportation. Therefore, to ensure safety, streamlined train operations, and uninterrupted internet access inside train tunnels, reliable wave propagation modeling is required. We have experimented and measured wave propagation models in a 1674 m long straight train tunnel in South Korea. The measured path loss and the received signal strength were modeled with the Close-In (CI), Floating intercept (FI), CI model with a frequency-weighted path loss exponent (CIF), and alpha-beta-gamma (ABG) models, where the model parameters were determined using minimum mean square error (MMSE) methods. The measured and the CI, FI, CIF, and ABG modelderived path loss was plotted in graphs, and the model closest to the measured path loss was identified through investigation. Based on the measured results, it was observed that every model had a comparatively lower (n < 2) path loss exponent (PLE) inside the tunnel. We also determined the path loss component's possible deviation (shadow factor) through a Gaussian distribution considering zero mean and standard deviation calculations of random error variables. The FI model outperformed all the examined models as it yielded a path loss closer to the measured datasets, as well as a minimum standard deviation of the shadow factor.

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“…There has been a huge effort in terms of accurate mathematical modeling and measuring campaigns to predict radio wave propagation in tunnels to ensure the good quality of communication links and increase the channel capacity. These are useful for vehicular networks, train applications, and even service and surveillance missions in both military and civilian contexts [ 4 , 5 , 6 , 7 , 8 ]. Deterministic channel models for tunnels include waveguide models, ray tracing models, and numerical methods for solving Maxwell’s equations in tunnel environments [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment

Halili

BniLam

Yusuf

et al. 2022

Sensors

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Most applications and services of Cooperative Intelligent Transport Systems (C-ITS) rely on accurate and continuous vehicle location information. The traditional localization method based on the Global Navigation Satellite System (GNSS) is the most commonly used. However, it does not provide reliable, continuous, and accurate positioning in all scenarios, such as tunnels. Therefore, in this work, we present an algorithm that exploits the existing Vehicle-to-Infrastructure (V2I) communication channel that operates within the LTE-V frequency band to acquire in-tunnel vehicle location information. We propose a novel solution for vehicle localization based on Doppler shift and Time of Arrival measurements. Measurements performed in the Beveren tunnel in Antwerp, Belgium, are used to obtain results. A comparison between estimated positions using Extended Kalman Filter (EKF) on Doppler shift measurements and individual Kalman Filter (KF) on Doppler shift and Time of Arrival measurements is carried out to analyze the filtering methods performance. Findings show that the EKF performs better than KF, reducing the average estimation error by 10 m, while the algorithm accuracy depends on the relevant RF channel propagation conditions and other in-tunnel-related environment knowledge included in the estimation. The proposed solution can be used for monitoring the position and speed of vehicles driving in tunnel environments.

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Modeling of radiowave propagation in tunnels

Cited by 5 publications

References 9 publications

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

Analysis and Modeling of Propagation in Tunnel at 3.7 and 28 GHz

Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment

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