Distributed Beamforming for Magnetic Induction Based Body Area Sensor Networks

Body Area Sensor Networks (BASNs) are a challenging research area with applications in healthcare and entertainment. Due to the importance of the target applications in the daily life, BASNs are a promising candidate for being included into the future Internet of Things (IoT). In particular, the dat...

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Bibliographic Details
Published in:2016 IEEE Global Communications Conference (GLOBECOM) pp. 1 - 7
Main Authors: Kisseleff, S., Akyildiz, I. F., Gerstacker, W.
Format: Conference Proceeding
Language:English
Published: IEEE 01-12-2016
Online Access:Get full text
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Summary:Body Area Sensor Networks (BASNs) are a challenging research area with applications in healthcare and entertainment. Due to the importance of the target applications in the daily life, BASNs are a promising candidate for being included into the future Internet of Things (IoT). In particular, the data gathering of the human activity may help customizing the services provided by the IoT and thus dramatically improve the IoT user experience. Magnetic Induction (MI) based communication is known in the context of wireless power transfer (WPT), near-field communication (NFC), and wireless sensor networks (WSNs) in challenging environments. In this approach, induction coils are utilized as antennas in the sensor nodes. Distributed beamforming is a well-known technique, that has been thoroughly investigated in the past. Here, the basic idea is to align the phases of signals from different sensor nodes in such a way that a virtual multiple-input multiple-output (MIMO) system with favorable properties is created. For example, this strategy may lead to an improved directionality of the transmitted signals and increase the achievable data rate. In this work, we analyze the potential of the distributed beamforming based MI-BASNs. We observe a significant increase of the achievable data rate for the proposed distributed beamforming compared to our selected baseline scheme.
DOI:10.1109/GLOCOM.2016.7841737