Impact of Rocks and Minerals on Underground Magneto-Inductive Communication and Localization

Abrudan, Traian E.; Kypris, Orfeas; Trigoni, Niki; Markham, Andrew

doi:10.1109/access.2016.2597641

Cited by 51 publications

(34 citation statements)

References 38 publications

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“…where E(·) is the expectation operator. To derive the diagonal elements of each sub-matrix, we put the value of P rj in (6) to (11) and solve it. Expression for the diagonal elements are obtained in Appendix A as follows…”

Section: ) Log-likelihood Ratio Calculationmentioning

confidence: 99%

3D Localization for Internet of Underground Things in Oil and Gas Reservoirs

Saeed¹,

Alouini²,

Al-Naffouri³

2019

IEEE Access

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Magnetic Induction (MI) is an efficient wireless communication method to deploy operational internet of underground things (IOUT) for oil and gas reservoirs. The IOUT consists of underground things which are capable of sensing the underground environment and communicating with the surface. The MI-based IOUT enable many applications, such as monitoring of the oil rigs, optimized fracturing, and optimized extraction. Most of these applications are dependent on the location of the underground things and therefore require accurate localization techniques. The existing localization techniques for MI-based underground sensing networks are two-dimensional and do not characterize the achievable accuracy of the developed methods which are both crucial and challenging tasks. Therefore, this paper presents the expression of the Cramer Rao lower bound (CRLB) for three-dimensional MI-based IOUT localization which takes into account the channel parameters of the underground magnetic-induction. The derived CRLB provide the suggestions for an MI-based underground localization system by associating the system parameters with the error trend. Numerical results demonstrate that localization accuracy is affected by different channel and networks parameters such as the number of anchors, noise variance, frequency, and the number of underground things.

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Section: ) Log-likelihood Ratio Calculationmentioning

confidence: 99%

3D Localization for Internet of Underground Things in Oil and Gas Reservoirs

Saeed¹,

Alouini²,

Al-Naffouri³

2019

IEEE Access

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“…However, to the best of our knowledge, no performance analysis of digital modulation schemes has been carried out in the electromagnetic (EM) based UG wireless communication channel. Capacity analysis [11], has been done for magneto-inductive (MI) based UG communications [1], [20], but it cannot be readily applied to IOUT because the spatial multipath modularity does not exist in MI, and sender-receiver coils have to be parallel to each other in MI-communications.…”

Section: Related Workmentioning

confidence: 99%

Wireless underground channel diversity reception with multiple antennas for internet of underground things

Salam

Vuran

2017

2017 IEEE International Conference on Communications (ICC)

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Internet of underground things (IOUT) is an emerging paradigm which consists of sensors and communication devices, partly or completely buried underground for real-time soil sensing and monitoring. In this paper, the performance of different modulation schemes in IOUT communications is studied through simulations and experiments. The spatial modularity of direct, lateral, and reflected components of the UG channel is exploited by using multiple antennas. First, it has been shown that bit error rates of 10 −3 can be achieved with normalized delay spreads (τ d) lower than 0.05. Evaluations are conducted through the first software-defined radio-based field experiments for UG channel. Moreover, equalization has a significant impact on the performance improvement of an IOUT system. An 8-Tap DFE (decision-feedback equalizer) adaptive equalizer achieves better performance. It is also found that DBPSK, and DPSK are more suitable for digital communications in the UG channel without adaptive equalization. Then, two novel UG receiver designs, namely, 3W-Rake and Lateral-Direct-Reflected (LDR) are developed and analyzed for performance improvement. It has been shown that with a three antenna LDR design, BER of lower than 10 −5 can be achieved. The BER of these two approaches are compared and the LDR has been shown to perform better.

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“…Internet of Underground Things (IOUT) have many applications in precision agriculture [1], [2], [5], [8], [10], [11], [12], [14], [15], [23], [25], [29], [21], [20], [22], [24], [16], [17], [18], [19], [34], [35], [36]. Border monitoring is another important application area of IOUT, where these networks are being used to enforce border and stop infiltration [3], [32].…”

Section: Introductionmentioning

confidence: 99%

Underground Environment Aware MIMO Design Using Transmit and Receive Beamforming in Internet of Underground Things

Salam

2019

Lecture Notes in Computer Science

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In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required derived the degrees of freedom of the UG MIMO interference channel. The underground receiver needs to perfectly cancel the interference from the three different components of the EM-waves propagating in the soil medium. This concept is based upon reducing the interference the undesired components to minimum at UG receiver using the receive beamforming. In this paper, underground environment aware MIMO using transmit and receive beamforming has been developed. The optimal transmit beamforming and receive combining vectors under minimal inter-component interference constraint are derived. It is shown that UG MIMO performs best when all three component of the wireless UG channel are leveraged for beamforming. The environment aware UG MIMO technique leads to threefold performance improvements and paves the wave for design and development of next generation sensor-guided irrigation systems in the field of digital agriculture.

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Impact of Rocks and Minerals on Underground Magneto-Inductive Communication and Localization

Cited by 51 publications

References 38 publications

3D Localization for Internet of Underground Things in Oil and Gas Reservoirs

3D Localization for Internet of Underground Things in Oil and Gas Reservoirs

Wireless underground channel diversity reception with multiple antennas for internet of underground things

Underground Environment Aware MIMO Design Using Transmit and Receive Beamforming in Internet of Underground Things

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