ArticleIET nanobiotechnology2019
Enhancing data rate of molecular communication system using Brownian motion.
Article in IET nanobiotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.Computational and mathematical methods in medicine · 2021Article
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3 authors.
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Abstract
Inter-symbol and co-channel interferences restrict the capacity of molecular communication (MC) systems. In this study, the effect of these interferences on the data rate of MC systems is investigated to design an efficient MC system. To this end, the authors propose an analytical model for a diffusion-based MC system comprised of two nanomachines when they exploit On/Off keying modulation. They model the Brownian motion of molecules in a one-dimensional environment as a wiener process and the life expectancy of diffused molecules as an exponential process. First, they consider the inter-symbol interference to derive the data rate of the MC system as a function of the receiver decision threshold and the symbol time duration. Hence, they propose an algorithm to obtain the optimal values of MC system parameters. Then, the effect of co-channel interference is considered by assuming parallel MC systems. They propose a minimum distance between adjacent MC systems that their co-channel interferences effect to be negligible. Moreover, they verify the accuracy of the analytical results by Monte-Carlo simulations. Results show a remarkable improvement in the data rate of MC systems. The derived results may find application in nanonetworks where nanomachines connect together to perform complex tasks.
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