Antenna Optimization for WBAN Based on Spherical Wave Functions De-Embedding

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Original languageEnglish
Pages (from-to)11033-11044
Number of pages12
JournalIEEE Transactions on Antennas and Propagation
Volume70
Issue number11
Publication statusPublished - 20 Jul 2022

Abstract

Antennas for wireless body area networks (WBANs) need to be modeled with adapted methods because the coupling with the body tissue does not allow for a clear separation between antenna and channel. Especially for dynamically varying on-body channels due to changing body poses, e.g., with head-worn antennas, modeling is challenging and design goals for optimal antennas are difficult to determine. Therefore, in this article, the modeling of WBAN channels using spherical wave functions (SWFs) is utilized for antenna de-embedding and for deriving optimal antenna characteristics that maximize the transmission coefficient for the respective channel. It is evaluated how typical factors influencing WBAN channels (different body anatomies, body postures, and varying positions of the communication nodes) can be modeled statistically with SWF. An optimized antenna design is developed based on the derived optimization method, specifically adapted to the channel of on-body links with eye-wear applications. The results with the optimized antenna are compared to other standard antenna designs and validated against measurements.

Keywords

    Antenna measurements, Antenna radiation patterns, Antennas, Body area networks, Receiving antennas, Transmitting antennas, Wireless communication, antenna de-embedding, implanted antennas, on-body propagation, spherical wave function (SWF), wearable antennas, wireless body area networks, wireless body area networks (WBANs), Antenna de-embedding

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Cite this

Antenna Optimization for WBAN Based on Spherical Wave Functions De-Embedding. / Berkelmann, Lukas; Jäschke, Hendrik; Mörlein, Leonardo et al.
In: IEEE Transactions on Antennas and Propagation, Vol. 70, No. 11, 20.07.2022, p. 11033-11044.

Research output: Contribution to journal › Article › Research › peer review

Berkelmann L, Jäschke H, Mörlein L, Grundmann L, Manteuffel D. Antenna Optimization for WBAN Based on Spherical Wave Functions De-Embedding. IEEE Transactions on Antennas and Propagation. 2022 Jul 20;70(11):11033-11044. doi: 10.48550/arXiv.2111.01708, 10.1109/TAP.2022.3191199
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title = "Antenna Optimization for WBAN Based on Spherical Wave Functions De-Embedding",
abstract = "Antennas for wireless body area networks (WBANs) need to be modeled with adapted methods because the coupling with the body tissue does not allow for a clear separation between antenna and channel. Especially for dynamically varying on-body channels due to changing body poses, e.g., with head-worn antennas, modeling is challenging and design goals for optimal antennas are difficult to determine. Therefore, in this article, the modeling of WBAN channels using spherical wave functions (SWFs) is utilized for antenna de-embedding and for deriving optimal antenna characteristics that maximize the transmission coefficient for the respective channel. It is evaluated how typical factors influencing WBAN channels (different body anatomies, body postures, and varying positions of the communication nodes) can be modeled statistically with SWF. An optimized antenna design is developed based on the derived optimization method, specifically adapted to the channel of on-body links with eye-wear applications. The results with the optimized antenna are compared to other standard antenna designs and validated against measurements.",
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author = "Lukas Berkelmann and Hendrik J{\"a}schke and Leonardo M{\"o}rlein and Lukas Grundmann and Dirk Manteuffel",
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AU - Grundmann, Lukas

AU - Manteuffel, Dirk

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