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A Semi-Analytical Method for Channel Modeling in Diffusion-Based Molecular Communication Networks.

Authors :
Zoofaghari, Mohammad
Arjmandi, Hamidreza
Etemadi, Ali
Balasingham, Ilangko
Source :
IEEE Transactions on Communications. Jun2021, Vol. 69 Issue 6, p3957-3970. 14p.
Publication Year :
2021

Abstract

Channel modeling is a challenging vital step towards the development of diffusion-based molecular communication networks (DMCNs). Analytical approaches for diffusion channel modeling are limited to simple and specific geometries and boundary conditions. Also, simulation- and experiment-driven methods are very time-consuming and computationally complex. In this paper, the channel model for DMCN employing the fundamental concentration Green’s function (CGF) is characterized. A general homogeneous boundary condition framework is considered that includes any linear reaction systems at the boundaries in the environment. To obtain the CGF for a general DMCN including multiple transmitters, receivers, and other objects with arbitrary geometries and boundary conditions, a semi-analytical method (SAM) is proposed. The CGF linear integral equation (CLIE) is analytically derived. By employing the numerical method of moments, the problem of CGF derivation from CLIE is transformed into an inverse matrix problem. Moreover, a sequential SAM is proposed that converts the inversion problem of a large matrix into multiple smaller matrices reducing the computational complexity. Particle-based simulator confirms the results obtained from the proposed SAM. The convergence and run time for the proposed method are examined. Further, the error probability of a simple diffusion-based molecular communication system is analyzed and examined using the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00906778
Volume :
69
Issue :
6
Database :
Academic Search Index
Journal :
IEEE Transactions on Communications
Publication Type :
Academic Journal
Accession number :
151250217
Full Text :
https://doi.org/10.1109/TCOMM.2021.3065372