Empowering Nanoscale Connectivity through Molecular Communication: A Case Study of Virus Infection

TL;DR

This paper investigates how molecular communication can model viral transmission and aid in epidemic control within the Internet of Bio-Nano Things, proposing detection, localization, and mutation identification strategies validated by simulations.

Contribution

It introduces a comprehensive framework for modeling viral spread via molecular communication, including detection, localization, and mutation identification methods, with validation through simulation.

Findings

MC channels modeled for macro and micro scales

Detection and localization methods developed for viruses

Mutation identification strategy validated by simulation

Abstract

The Internet of Bio-Nano Things (IoBNT), envisioned as a revolutionary healthcare paradigm, shows promise for epidemic control. This paper explores the potential of using molecular communication (MC) to address the challenges in constructing IoBNT for epidemic prevention, specifically focusing on modeling viral transmission, detecting the virus/infected individuals, and identifying virus mutations. First, the MC channels in macroscale and microscale scenarios are discussed to match viral transmission in both scales separately. Besides, the detection methods for these two scales are also studied, along with the localization mechanism designed for the virus/infected individuals. Moreover, an identification strategy is proposed to determine potential virus mutations, which is validated through simulation using the ORF3a protein as a benchmark. Finally, open research issues are discussed. In summary, this paper aims to analyze viral transmission through MC and combat viral spread using signal processing techniques within MC.