Mathematical Channel Modeling of Electromagnetic Waves in Biological Tissues for Wireless Body Communication

Intissar Krimi, Sofiane Ben Mbarek, Selma Amara, Fethi Choubani, Yehia Mahmoud Massoud

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


In the wireless body area network (WBAN), radio propagations from devices that communicate with the human body are very complex and distinctive compared to other environments. As we know, the human body is a lossy channel that significantly attenuates the propagation of electromagnetic waves (EMW). Therefore, channel models are critical in evaluating the communication link. One of the most predominant models is the path loss channel model, which is used to cover a wide range of communication channels and frequency bands in WBAN. This paper investigates the EMW in a human model irradiated by an incident electromagnetic plane wave. A planar multilayer structure is used for modeling human tissue. Moreover, the steady-state electromagnetic distribution is calculated by solving the differential and integral equations (DIE) by using the method of moments (MoM). The obtained results demonstrate the great use of performing a theoretical analysis for path loss (PL) and power loss density (PLD) estimation. The magnitude of the electric field inside muscle tissue at various depths, and with the most important frequencies in medical applications, is evaluated. This investigation provides evidence that the penetration of EMW in biological tissue strongly depends on the frequency and thickness of the tissue involved. Thus, for different examined conditions, an excellent agreement between recent results that were obtained by an analytical method, finite element (FEM), and the proposed MoM method is verified to be valid in this investigation, and it is found that the distribution of the field, PL, and PLD for different communication scenarios is very promising to determine the quality of communication for WBAN technology.
Original languageEnglish (US)
Pages (from-to)1282
Issue number6
StatePublished - Mar 7 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-03-13
Acknowledgements: This research received no external funding.


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