Autoencoder-Based Transceivers for Multiple Access Human Body Communication Networks

The Internet of Bodies (IoB) represents a transformative technological innovation that merges the bio-physical and digital realms through networks of intelligent devices positioned in, on, and around the human body. Human Body Communication (HBC) offers a promising method for enabling IoB networks, using the human body as a communication channel for multiple wearable nodes. Despite the prevalence of HBC peer-to-peer communication methods in the literature, the challenge of implementing multiple access techniques for HBC at the physical layer remains largely unexplored. In this paper, we propose a new multiple access HBC (MA-HBC) system that leverages autoencoders to design and implement low-power and efficient transceivers sharing a common channel. The proposed MA-HBC system consists of multiple autoencoder-based transceivers trained jointly to optimize overall network performance. It supports various data rates ranging from 164 kbps to 5.25 Mbps, making it suitable for a wide range of IoB applications. To validate the design, a prototype implementation is presented. Additionally, to ensure suitability for wearable devices, a low-power hardware transceiver architecture is provided with an estimated energy efficiency of 105 pJ/b when implemented using TSMC 65nm LP technology. The results show that the proposed MA-HBC system outperforms traditional IEEE 802.15.6 based transceivers for two users with time Sharing, achieving a 3.9 dB improvement in Signal-to-Noise Ratio (SNR) at a block error rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{-2}$</tex-math> </inline-formula>.

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Publication Details

Journal
IEEE Transactions on Circuits and Systems I Regular Papers
Published
2025-06-27
DOI
https://doi.org/10.1109/tcsi.2025.3582415
Citations
3
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
2.02
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article

Autoencoder-Based Transceivers for Multiple Access Human Body Communication Networks

Ahmed M. Eltawil, Abdulkadir Çelik, Abdelhay Ali, Amr N. Abdelrahman
3 citations
IEEE Transactions on Circuits and Systems I Regular Papers
Wireless Body Area Networks
2.02
article

Autoencoder-Based Transceivers for Multiple Access Human Body Communication Networks

Ahmed M. Eltawil, Abdulkadir Çelik, Abdelhay Ali, Amr N. Abdelrahman
article en
3 citations

Abstract

The Internet of Bodies (IoB) represents a transformative technological innovation that merges the bio-physical and digital realms through networks of intelligent devices positioned in, on, and around the human body. Human Body Communication (HBC) offers a promising method for enabling IoB networks, using the human body as a communication channel for multiple wearable nodes. Despite the prevalence of HBC peer-to-peer communication methods in the literature, the challenge of implementing multiple access techniques for HBC at the physical layer remains largely unexplored. In this paper, we propose a new multiple access HBC (MA-HBC) system that leverages autoencoders to design and implement low-power and efficient transceivers sharing a common channel. The proposed MA-HBC system consists of multiple autoencoder-based transceivers trained jointly to optimize overall network performance. It supports various data rates ranging from 164 kbps to 5.25 Mbps, making it suitable for a wide range of IoB applications. To validate the design, a prototype implementation is presented. Additionally, to ensure suitability for wearable devices, a low-power hardware transceiver architecture is provided with an estimated energy efficiency of 105 pJ/b when implemented using TSMC 65nm LP technology. The results show that the proposed MA-HBC system outperforms traditional IEEE 802.15.6 based transceivers for two users with time Sharing, achieving a 3.9 dB improvement in Signal-to-Noise Ratio (SNR) at a block error rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{-2}$</tex-math> </inline-formula>.

IEEE Transactions on Circuits and Systems I Regular PapersVol. 72(12)
University of Southampton (GB), King Abdullah University of Science and Technology (SA)
Openalex Percentile: Top 13%
Wireless Body Area Networks
2.02
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