DocumentCode :
2367663
Title :
Adaptive tuning method for maximizing capacity in magnetic induction communication
Author :
Lee, Kisong ; Cho, Dong-Ho
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
4310
Lastpage :
4314
Abstract :
Sensors are embedded in dense mediums, such as walls of building and underground, for various applications. However, traditional wireless communication using electromagnetic (EM) waves does not operate well in this embedded sensor networks because the EM waves are attenuated severely in new propagation mediums including rock, soil, and water. Magnetic induction (MI) communication is rising as a promising technique for embedded sensor networks since the magnetic field experiences little attenuation in dense mediums. In this paper, we investigate the capacity maximization of MI communication. First, in strongly coupled scenario, we find the splitting coupling point from an equivalent circuit model to investigate frequency splitting problem. In loosely coupled scenario, optimal quality factor for maximizing the capacity is derived from the channel model of MI communication. Finally, we show the consistency of our analytic results and the effectiveness of the proposed algorithm through numerical results.
Keywords :
Q-factor; channel capacity; electromagnetic induction; electromagnetic wave propagation; equivalent circuits; intelligent sensors; underground communication; wireless sensor networks; EM waves; MI communication; adaptive tuning method; capacity maximization; channel model; electromagnetic waves; embedded sensor networks; equivalent circuit model; frequency splitting problem; magnetic field; magnetic induction communication; optimal quality factor; propagation mediums; rock; soil; splitting coupling point; water; wireless communication; wireless underground sensor networks; Coils; Couplings; Q factor; Resistors; Resonant frequency; Sensors; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2012 IEEE International Conference on
Conference_Location :
Ottawa, ON
ISSN :
1550-3607
Print_ISBN :
978-1-4577-2052-9
Electronic_ISBN :
1550-3607
Type :
conf
DOI :
10.1109/ICC.2012.6363905
Filename :
6363905
Link To Document :
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