Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Channel Modeling for In-body Optical Wireless Communications

Version 1 : Received: 3 November 2021 / Approved: 5 November 2021 / Online: 5 November 2021 (10:38:49 CET)

How to cite: Trevlakis, S.E.; Boulogeorgos, A.A.; Chatzidiamantis, N.D.; Karagiannidis, G.K. Channel Modeling for In-body Optical Wireless Communications. Preprints 2021, 2021110114 (doi: 10.20944/preprints202111.0114.v1). Trevlakis, S.E.; Boulogeorgos, A.A.; Chatzidiamantis, N.D.; Karagiannidis, G.K. Channel Modeling for In-body Optical Wireless Communications. Preprints 2021, 2021110114 (doi: 10.20944/preprints202111.0114.v1).

Abstract

Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognised in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different type of tissues. Towards this direction, in this paper we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues’ constituents, namely fat, water, melanin, oxygenated and de-oxygenated blood. Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue. Next, by incorporating the impact of scattering in the aforementioned model we formulate the complete pathloss model. The developed theoretical framework is verified by means of comparisons between the estimated pathloss and experimental measurements from independent research works. Finally, we illustrate the accuracy of the theoretical framework in estimating the optical properties of any generic tissue based on its constitution. The extracted channel model is capable of boosting the design of optimized communication protocols for a plethora of biomedical applications.

Keywords

Absorption coefficient; biomedical engineering; fitting; machine learning; optical properties; pathloss; scattering coefficient.

Subject

ENGINEERING, Electrical & Electronic Engineering

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