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Comparative analysis of magnetic induction based communication techniques for wireless underground sensor networks

Taylor & Francis
PeerJ Computer Science
Authors:
Rishi pal Singh at Guru Jambheshwar University of Science & Technology
Rishi pal Singh
Pratap Singh
Pratap Singh
Pratap Singh
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Yudhvir Singh at Maharshi Dayanand University
Yudhvir Singh
Mohamed Abouhawwash at Mansoura University
Mohamed Abouhawwash
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Abstract

A large range of applications have been identified based upon the communication of underground sensors deeply buried in the soil. The classical electromagnetic wave (EM) approach, which works well for terrestrial communication in air medium, when applied for this underground communication, suffers from significant challenges attributing to signal absorption by rocks, soil, or water contents, highly varying channel condition caused by soil characteristics, and requirement of big antennas. As a strong alternative of EM, various magnetic induction (MI) techniques have been introduced. These techniques basically depend upon the magnetic induction between two coupled coils associated with transceiver sensor nodes. This paper elaborates on three basic MI communication mechanisms i.e . direct MI transmission, MI waveguide transmission, and 3D coil MI communication with detailed discussion of their working mechanism, advantages and limitations. The comparative analysis of these MI techniques with each other as well as with EM wave method will facilitate the users in choosing the best method to offer enhanced transmission range (upto 250 m), reduced path loss (<100 dB), channel reliability, working bandwidth (1–2 kHz), & omni-directional coverage to realize the promising MI-based wireless underground sensor network (WUSN) applications.
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... The acoustic waves can reach distances of a few tens of meters underground [36], but the very low data rate, high noise levels and delays limit their uses in WUSNs [30,75]. The technologies based on magnetic induction (MI) are limited in terms of communication distance of about a few meters [55][56][57][58][59]. Ref. [60] proposed to install some relays composed of small transmitter and receiver coils to ensure the magnetic waves continuity, but the accurate orientation of the coils is difficult to carry out in practice. ...
... [36] -Present a system based on acoustic waves [39] -Develop and evaluate a path loss model [37] -Study the propagation characteristic of EM waves Routing [43] -Propose a routing protocol for WUSN [46] -Optimize the power of the relay node on WUSN [44] -Use cluster-based cooperative models [45] -Deploy relay nodes to prolong network lifetime [40] -Description of a single-hop approach in WUSN [41] -Study the optimal placement of the relay nodes Energy [49] -Analyze the energy consumption of different networks [50] -Study the wake-up of buried sensor nodes [48] -Propose multi-hoped communications guarantying energy efficiency [47] -Present energy harvesting approaches for WUSN Antenna [53] -Study the impacts of moisture on antenna return loss and bandwidth [54] -Model the antenna return loss face to moisture variations [51] -Present a design of phased array antennas [52] -Study the impact of soil on UWB antenna MI [55] -Analyze the multi-hop underground communications based on MI [56] -Investigate MI communications based on relay circuits [57] -Propose a routing protocol for WUSN based on MI [58] -Compare the communications based on MI and EM waves [59] -Present the challenges of MI communications in WUSN [60] -Compare the communications based on MI and EM waves ...
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... The channel quality parameters are uncommon for different types of WUGSN mediums established for underground transmission, underground to surface transmission, and surface to base station transmission [3][4][5]. In this case, the channel parameter analysis model needs suitable channel quality management principles, adaptive learning functions, and reactive backing systems [6,7]. The recent development in computing arena initiates the variants of Machine Learning (ML) and Deep Learning (DL) frameworks to make intelligent decisions against critical problems. ...
... The underground sensor signals are affected due to reflection, absorption, refraction, and scattering of electromagnetic signals. The receiving power at different links are derived as provided in Equations (5)- (7). ...
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