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Enhancing data rate of molecular communication system using Brownian motion
Keyvan Aghababaiyan1, Reza Ghaderi Zefreh2, Vahid Shah-Mansouri3
1School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14395-515, Iran. aghababaiyan@ut.ac.ir.
IET Nanobiotechnology
|May 5, 2019
Summary
This study models interference in molecular communication (MC) systems to boost data rates. An optimized analytical model and distance parameters improve MC system efficiency for nanonetworks.
Area of Science:
- Molecular Communication
- Biophysics
- Information Theory
Background:
- Inter-symbol and co-channel interference limit molecular communication (MC) system capacity.
- Designing efficient MC systems requires understanding and mitigating these interference effects.
Purpose of the Study:
- To investigate the impact of inter-symbol and co-channel interference on MC system data rates.
- To develop an analytical model for optimizing diffusion-based MC systems using On/Off keying modulation.
- To propose solutions for enhancing MC system performance in nanonetwork applications.
Main Methods:
- Developed an analytical model for a two-nanomachine diffusion-based MC system.
- Modeled molecular Brownian motion as a Wiener process and molecule lifespan as an exponential process.
- Derived data rate based on receiver threshold and symbol duration; proposed an optimization algorithm.
- Assessed co-channel interference by considering parallel MC systems and determining minimum separation distances.
- Validated analytical results using Monte-Carlo simulations.
Main Results:
- An analytical model was established for inter-symbol interference in diffusion-based MC systems.
- An algorithm was proposed to optimize MC system parameters, enhancing data rate.
- A minimum distance was identified to minimize co-channel interference effects between adjacent MC systems.
- Monte-Carlo simulations confirmed the accuracy of the analytical findings.
Conclusions:
- The study successfully modeled and analyzed interference in MC systems.
- Proposed methods significantly improve the data rate of MC systems.
- Findings are applicable to nanonetworks, enabling more complex tasks through interconnected nanomachines.
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