Adaptive tuning method for maximizing capacity in magnetic induction communication

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.