Terahertz fading model for wireless nanosensor networks in advanced medical manufacturing technologies

Ibrahim Tariq Javed, Kashif Naseer Qureshi, Fares Alharbi, Gwanggil Jeon

Research output: Contribution to journalArticlepeer-review

Abstract

Nanomaterials such as graphene have allowed the manufacturing of different types of nanosensors. These nanosensors will sense and stimulate action, store, and process the data and transmit electromagnetic signals in the terahertz range. Enabling communication will allow nanosensors to form a network that will lead to various applications in different fields, especially in advanced manufacturing technologies and biomedical. However, the signal propagated by nanoantennas in terahertz gets attenuated by molecules present in the medium, such as the human body. This paper presents a simple fading model for wireless nanosensor networks for advanced manufacturing technologies and applications that incorporates molecular absorption and molecular noise. The model estimates the log-distance path loss model with random attenuation caused by the molecules present in the medium. It has been observed that the water molecule present inside the human body produces significant attenuation to terahertz frequencies. The path loss model presented has been used to identify certain frequency windows within the terahertz band that can be used for communication purposes in nanoapplications. For instance, a 400-GHz wideband from 100 to 500 GHz has been identified with a mean attenuation of 0.021 dB/cm inside the human body. Furthermore, channel capacity is computed for these bands that shows the specified bands achieve better throughput than those with more significant molecular attenuation.

Original languageEnglish
Pages (from-to)5175
Number of pages1
JournalInternational Journal of Advanced Manufacturing Technology
Volume132
Issue number9-10
DOIs
Publication statusPublished - Jun 2024
Externally publishedYes

Keywords

  • Channel capacity
  • Channel modelling
  • Graphene
  • Wireless nanosensor networks

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