期刊
IEEE TRANSACTIONS ON COMMUNICATIONS
卷 69, 期 6, 页码 3957-3970出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2021.3065372
关键词
Receivers; Transmitters; Geometry; Boundary conditions; Analytical models; Molecular communication (telecommunication); Green's function methods; Diffusion Processes; molecular communications; channel models; Green's second identity; method of moments
资金
- European Research Consortium for Informatics and Mathematics (ERCIM)
- Research Council of Norway (RCN:CIRCLE-Communication Theoretical Foundation of Wireless Nanonetworks) [287112]
Channel modeling is a crucial step in the development of diffusion-based molecular communication networks. This paper proposes a new method based on concentration Green's function, utilizing a semi-analytical approach to model channels in DMCNs with multiple transmitters, receivers, and other objects. Experimental results confirm the accuracy and efficiency of the proposed method, showing high convergence and computational performance.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据