Influence of Red Blood Cells on Channel Characterization in Cylindrical Vasculature.

IF 3.7 4区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Kathan S Joshi, Dhaval K Patel, Shivam Thakker, Miguel Lopez-Benitez, Janne J Lehtomaki
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引用次数: 0

Abstract

Molecular communication via diffusion (MCvD) expects Brownian motions of the information molecules to transmit information. However, the signal propagation largely depends on the geometric characteristics of the assumed flow model, i.e., the characteristics of the environment, design, and position of the transmitter and receiver, respectively. These characteristics are assumed to be lucid in many ways by either consideration of one-dimensional diffusion, unbounded environment, or constant drift. In reality, diffusion often occurs in blood-vessel-like channels. To this aim, we try to study the effect of the biological environment on channel performance. The Red-Blood Cells (RBCs) found in blood vessels enforces a higher concentration of molecules towards the vessel walls, leading to better reception. Therefore, in this paper we derive an analytical expression of Channel Impulse Response (CIR) for a dispersion-advection-based regime, contemplating the influence of RBCs in the model and considering a point source transmitter and a realistic design of the receiver.

红细胞对圆柱形血管中通道特性的影响
通过扩散进行的分子通讯(MCvD)希望通过信息分子的布朗运动来传输信息。然而,信号传播在很大程度上取决于假定流动模型的几何特征,即环境特征、设计以及发射器和接收器的位置。通过考虑一维扩散、无边界环境或恒定漂移等多种方式,这些特征被假定为是清晰的。实际上,扩散通常发生在类似血管的通道中。为此,我们尝试研究生物环境对通道性能的影响。血管中的红血细胞(RBC)会使分子向血管壁集中,从而导致更好的接收效果。因此,在本文中,我们推导出了基于色散-平流机制的信道脉冲响应(CIR)的分析表达式,在模型中考虑了红血细胞的影响,并考虑了点源发射器和接收器的实际设计。
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来源期刊
IEEE Transactions on NanoBioscience
IEEE Transactions on NanoBioscience 工程技术-纳米科技
CiteScore
7.00
自引率
5.10%
发文量
197
审稿时长
>12 weeks
期刊介绍: The IEEE Transactions on NanoBioscience reports on original, innovative and interdisciplinary work on all aspects of molecular systems, cellular systems, and tissues (including molecular electronics). Topics covered in the journal focus on a broad spectrum of aspects, both on foundations and on applications. Specifically, methods and techniques, experimental aspects, design and implementation, instrumentation and laboratory equipment, clinical aspects, hardware and software data acquisition and analysis and computer based modelling are covered (based on traditional or high performance computing - parallel computers or computer networks).
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