An Underwater Acoustic Channel Modeling for Internet of Things Networks
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An Underwater Acoustic Channel Modeling for Internet of Things Networks Ho Kyoung Lee1 · Byung Moo Lee2
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Interest in wideband and medium distance underwater acoustic communication systems is increasing due to the practical application of underwater Internet of Things (IoT) networks. In this paper, we propose a simplified empirical channel model for the medium distance underwater acoustic channels based on real measurement results. The simple and tractable channel model is critical for the development of advanced underwater communications technology. The underwater channel measurements were performed at 20 m sea water depth, the transmitters (TXs) were located at 5 m and 15 m from the bottom, the receivers (RXs) were located at 4 m, 8 m, 12 m, and 16 m from the bottom, and the TX–RX distances were 21 m, 71 m, 127 m, and 273 m. We derived the path loss from the measured dataset, and modified the log-distance model to create a model suitable for an underwater IoT channel. Numerical results show that the proposed model is accurate and reliable enough to use in the development of advanced underwater communication technologies. Keywords Underwater · Internet of Things (IoT) · Channel model · Path loss
1 Introduction Underwater communication is a traditional research topic upon which many studies have been conducted so far [1–5]. Generally, underwater communication uses acoustic signals with relatively narrowband (typically 10–20 kHz) due to the seriousness of the attenuation and low pass filtering effect. Underwater sound propagates with very low speed (around 1500 m/s) and suffers severe multipath due to high delay spread. Moreover, the transmitter (TX), receiver (RX), and surface motion create an extreme Doppler effect [2]. For all of the aforementioned reasons, modeling of an underwater acoustic channel is quite difficult. Nowadays, the attention to the relatively wideband and medium-short distance underwater communication is growing. Here wideband and medium-short distance indicate more than 30 kHz bandwidth and 10–300 m distance. Underwater activities continually increase not only for the enjoyment of leisure time, but also for many underwater tasks using robots. * Byung Moo Lee [email protected] 1
School of Electronic and Electrical Engineering, Hongik University, Seoul 04066, South Korea
2
School of of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, South Korea
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H. K. Lee, B. M. Lee
Based on these activities, underwater Internet of things (IoT) network is also being studied very actively [3, 5]. IoT networks have features include big data based on cloud computing, IoT network management, edge computing, and so on. In [6], the authors provided a functional framework that identifies the acquisition, management, processing and mining areas of IoT big data, and several associated technical modules were defined and described in terms of their key characteristics and capabilities.
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