Influence of Mine Tunnel Wall Humidity on Electromagnetic Waves Propagation

Cheng, Lingfei; Zhang, Lili; Li, Jie

doi:10.1155/2012/734379

Cited by 5 publications

(5 citation statements)

References 1 publication

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“…The solution is particularly suitable for the frequencies at which the signal wavelength is comparable with the tunnel cross section dimension [92]. The humidity of tunnel walls affects the conductivity and dielectric constant and consequently also the attenuation of electromagnetic wave propagation [93]. Measurements show negligible effect of humidity on the dielectric constant, while the effect of humidity on the conductivity cannot be ignored [47].…”

Section: B Electromagnetic Properties Of Tunnel Wallsmentioning

confidence: 99%

A Survey of Radio Propagation Modeling for Tunnels

Hrovat

Kandus

Javornik

2014

IEEE Commun. Surv. Tutorials

180

107

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Radio signal propagation modeling plays an important role in designing wireless communication systems. The propagation models are used to calculate the number and position of base stations and predict the radio coverage. Different models have been developed to predict radio propagation behavior for wireless communication systems in different operating environments. In this paper we shall limit our discussion to the latest achievements in radio propagation modeling related to tunnels. The main modeling approaches used for propagation in tunnels are reviewed, namely, numerical methods for solving Maxwell equations, waveguide or modal approach, ray tracing based methods and two-slope path loss modeling. They are discussed in terms of modeling complexity and required information on the environment including tunnel geometry and electric as well as magnetic properties of walls.

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Section: B Electromagnetic Properties Of Tunnel Wallsmentioning

confidence: 99%

A Survey of Radio Propagation Modeling for Tunnels

Hrovat

Kandus

Javornik

2014

IEEE Commun. Surv. Tutorials

180

107

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“…It is found that surface roughness of tunnel walls introduces additional power attenuation to radio signals. Moreover, the influence of humidity in conductivity and dielectric constant has been considered [52]. The results show that there is negligible effect on the dielectric constant, but not on conductivity.…”

Section: Parameters Influencing Radio Propagation Inside Tunnelmentioning

confidence: 99%

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

Liu

Ghazal

Wang

et al. 2017

Sci. China Inf. Sci.

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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.Keywords 5G, HST, tunnel scenarios, tunnel channel measurements, tunnel channel models, non-stationary statistical properties. CitationLiu Y, Ghazal A, Wang C X, et al. Channel measurements and models for high-speed train wireless communication systems in tunnel scenarios: a survey. Sci China Inf Sci, 2016, 59(1): xxxxxx, doi: xxxxxxxxxxxxxx IntroductionHigh-speed trains (HSTs) have experienced a rapid development recently [1], and wireless technologies for HST communications will be considered as an important issue in the fifth generation (5G) wireless communication networks [2]. With the number of HST users increasing, numerous communication data need to be transmitted to train passengers through wireless channels. Therefore, high-capacity and reliable HST communication networks regardless of users' locations or speeds, are required. In order to meet these requirements, HST wireless communication systems need to mitigate various challenges resulting from the high * Corresponding author (email: cheng-xiang.wang@hw.ac.uk) 2 Liu Y, et al. Sci China Inf Sci speed of the train, such as frequent handovers, large Doppler spreads, and fast travel through different HST scenarios [3]. Currently, the most widely used HST communication system is the Global System for Mobile Communication Railway (GSM-R) [4]. It can be used for the train communication and control. However, it cannot satisfy the increasing communication requirements of high data rates. In recent years, the Long-Term Evolution-Railway (LTE-R) system, which is based on the LTE-Advanced (LTE-A) system, has been recommended to replace the GSM-R. Both of them adopted the conventional network architecture in which HST users inside the train communicate with outdoor base stations (BSs) directly. However, such an architecture results in high penetration losses when the signals travel into the carriages and leads to a spotty coverage, which will result in the handover failure or the high drop calls rate [4]. To overcome the above problems, the promising mobile relay station (MRS) solution has been proposed for future HST communication systems to solve the spotty coverage problem and mitigate ...

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“…The degree of channel humidity has an effect on the propagation the signal undergoes in this channel. Mine tunnel rock is composed of spherical particles and rock pores [10]. When the holes among particles are full of water, thus in the presence of high humidity, the rock permittivity increases with water saturation and decreases with the frequency [10].…”

Section: Experimental Setup Processmentioning

confidence: 99%

“…Mine tunnel rock is composed of spherical particles and rock pores [10]. When the holes among particles are full of water, thus in the presence of high humidity, the rock permittivity increases with water saturation and decreases with the frequency [10]. The impact of humidity on the conductivity of tunnel walls is more complex and calls for the concept of conductivity breakpoint and the pore water conductivity.…”

Section: Experimental Setup Processmentioning

confidence: 99%

“…When this latter is low, the conductivity of walls cannot reach the conductivity breakpoint, whatever the walls humidity, thus rendering the effect of humidity on electromagnetic propagation negligible. When the pore water conductivity is high, the walls conductivity increases as the level of humidity increases, and if it reaches the breakpoint, will imply a significant attenuation of the electromagnetic propagation [10]. Our collected channel measurements encompass the effects of humidity, multipath and walls ceiling and floor compositions.…”

Section: Experimental Setup Processmentioning

confidence: 99%

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On the Performance Enhancement When Combining STBC and Channel Estimation Techniques in Underground MIMO Channels

Boualleg

Ghanem

Haraoubia

et al. 2016

Antennas Wirel. Propag. Lett.

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One way to enhance the channel data rate in enclosed environments is by incorporating Multiple Input Multiple Output (MIMO) systems. Very often, this comes at the cost of data reliability. Motivated by the proven efficiency of Space Time Block Coding (STBC) technique in conventional MIMO systems in improving the communication quality, we propose to incorporate it in wireless underground MIMO communication system and investigate data reliability at the reception in terms of bit error rate (BER). For this purpose, an intensive channel measurement campaign was performed in a mine-laboratory in Northern Canada to obtain the perfect channel state. As a second step, the underground MIMO channel is estimated by sending a pilot sequence and using minimum mean square error (MMSE) principle on the received pilots. The resulting MIMO channel estimate is used to evaluate the data part in the STBC block and perform a decision using the maximum likelihood (ML) detector. Moreover, both the channel and transmitted data estimates are given analytically and the degradation of the BER performance of the system due to MMSE estimation errors is studied using Monte Carlo simulations.

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Influence of Mine Tunnel Wall Humidity on Electromagnetic Waves Propagation

Cited by 5 publications

References 1 publication

A Survey of Radio Propagation Modeling for Tunnels

A Survey of Radio Propagation Modeling for Tunnels

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

On the Performance Enhancement When Combining STBC and Channel Estimation Techniques in Underground MIMO Channels

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