A Survey of Wireless Communications and Propagation Modeling in Underground Mines

Forooshani, Arghavan Emami; Bashir, Shahzad; Michelson, David G.; Noghanian, Sima

doi:10.1109/surv.2013.031413.00130

Cited by 183 publications

(139 citation statements)

References 64 publications

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“…Radio Propagation model through the tunnel. The radio propagation behaviour in the tunnel-like environment has been studied and reported in the literature [18][19][20][21]. Next there are several distributions for modelling the wave path loss; namely, Rayleigh, Nakagami, Rice, Weibull and log-normal shadowing are among the most commonly used models.…”

Section: Figure 1 Overview Of the Methodologymentioning

confidence: 99%

“…For our simulation purpose, we choose Ray-Tracing model considering one reflection for propagation modelling; and for path loss to used log-distance path loss model. Compared to other models we prefered Ray-Tracing model for its mathematical simplicity [18] and ease of implementation fir the simulated cases. Coefficient used in the radio propagation model were derived from experimental readings, for reproduction of this work in some real mine or underground tunnel, an experimentally developed RSSI map can be used.…”

Section: Figure 1 Overview Of the Methodologymentioning

confidence: 99%

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Investigation of wireless tracking performance in the tunnel-like environment with particle filter

Halder¹,

Chakravarty²

2018

MMEP

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When the basic nonlinear filtering problem for dynamic systems is considered, in such case, the particle filter is one of the suitable methods that has perhaps become one of the most commonly used methods in recent years. Positioning or localization falls under such a nonlinear filtering problem. Positioning is a matter of interest for both domestic and industrial application, due to its potential use in wide range of context-aware services that it can enable by leveraging the Internet of Things approach. However, in areas where GPS signals are not available such as underground tunnel roadways, where the localization is done mostly using radio beacons. This study mathematically simulates tracking operation in such a tunnel-like situation and studied the position estimation by the particle filter. From the results, we were able to visualize how varying different configuration parameters affect the estimation accuracies and also get an idea of worst-case estimates by seeing its standard deviation of estimated positions for different instances of repeated experiments. And our results also confirmed that deploying additional beacons have a contribution to the improvement in error tolerance. However, the improvements are significantly notable only around the point where beacon has been added. When the basic nonlinear filtering problem for dynamic systems is considered, in such case, the particle filter is one of the suitable methods that has perhaps become one of the most commonly used methods in recent years. Positioning or localization falls under such a nonlinear filtering problem. Positioning is a matter of interest for both domestic and industrial application, due to its potential use in wide range of context-aware services that it can enable by leveraging the Internet of Things approach. However, in areas where GPS signals are not available such as underground tunnel roadways, where the localization is done mostly using radio beacons. This study mathematically simulates tracking operation in such a tunnel-like situation and studied the position estimation by the particle filter. From the results, we were able to visualize how varying different configuration parameters affect the estimation accuracies and also get an idea of worst-case estimates by seeing its standard deviation of estimated positions for different instances of repeated experiments. And our results also confirmed that deploying additional beacons have a contribution to the improvement in error tolerance. However, the improvements are significantly notable only around the point where beacon has been added.

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Section: Figure 1 Overview Of the Methodologymentioning

confidence: 99%

Section: Figure 1 Overview Of the Methodologymentioning

confidence: 99%

Investigation of wireless tracking performance in the tunnel-like environment with particle filter

Halder¹,

Chakravarty²

2018

MMEP

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“…Despite the mining industry reliance on wireless communications, radio propagation in surface mines has not been explored as extensively as in underground mines [8]. In the case of open-pit mines, only a limited set of references was found.…”

Section: Introductionmentioning

confidence: 99%

5G in Open-Pit Mines: Considerations on Large-Scale Propagation in Sub-6 GHz Bands

Almeida

Caldwell²,

Rodríguez

et al. 2017

2017 IEEE Globecom Workshops (GC Wkshps)

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Abstract-5G will play a pivotal role in the digitization of the industrial sector and is expected to make the best use of every bit of spectrum available. In this light, this paper presents the results of an extensive measurement campaign in two iron-ore open-pit mining complexes, at the 700 MHz and 2.6 GHz bands, considering macro and small cell deployments. The study is further motivated by the rise of unmanned machinery in the mining industry. We present values of path loss exponents, shadow fading standard deviations, autocorrelation distances and inter-frequency crosscorrelation, which are all useful for the future wireless network design, simulation and performance evaluation. The results show that, in order to comply with ultra-reliable communications (URC) availability requirements, larger shadowing margins will have to be considered in the network planning in open-pit mines, when compared to traditional industrial environments. Furthermore, large cross-correlation between the shadowing in both frequency bands limits the gains when using multi-connectivity in order to enhance overall network availability.

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“…Typically these locations are fraught with multiple natural and industrial hazards. Therefore, there is a need to deploy wireless sensor networks to monitor events (i.e., structural integrity, dangerous chemicals, and health of workers) [1], [2]. Wireless communication and sensory equipment are constrained by electrical safety, hostile propagation environment, electromagnetic (EM) noise in these environments.…”

Section: Introductionmentioning

confidence: 99%

“…The challenge in subterranean (i.e., tunnels and mines) and industrial confined environments (i.e., pipe networks) is that the propagation pathloss for EM waves can be very high. For example, in tunnels and underground mines, the pathloss distance exponent can be greater than 4 for a wide range of radio frequencies (0.9 to 2.4 GHz) [2]. When the pipe or tunnel network can not act as a wave-guide for the data bearing EM wave, the pathloss is even greater [3].…”

Section: Introductionmentioning

confidence: 99%

A molecular communication link for monitoring in confined environments

Qiu

Guo

Wang

et al. 2014

2014 IEEE International Conference on Communications Workshops (ICC)

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A Survey of Wireless Communications and Propagation Modeling in Underground Mines

Cited by 183 publications

References 64 publications

Investigation of wireless tracking performance in the tunnel-like environment with particle filter

Investigation of wireless tracking performance in the tunnel-like environment with particle filter

5G in Open-Pit Mines: Considerations on Large-Scale Propagation in Sub-6 GHz Bands

A molecular communication link for monitoring in confined environments

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