Research Article
A vertical channel model of molecular communication and its test-bed
@ARTICLE{10.4108/eai.21-3-2017.152390, author={Pengfei Lu and Zhenqiang Wu and Bo Liu}, title={A vertical channel model of molecular communication and its test-bed}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={3}, number={9}, publisher={EAI}, journal_a={PHAT}, year={2017}, month={3}, keywords={Gravity, molecular communication, non-linear least squares method, test-bed, vertical channel model}, doi={10.4108/eai.21-3-2017.152390} }
- Pengfei Lu
Zhenqiang Wu
Bo Liu
Year: 2017
A vertical channel model of molecular communication and its test-bed
PHAT
EAI
DOI: 10.4108/eai.21-3-2017.152390
Abstract
The study of molecular communication is more and more prevalence, and channel model of molecular communication plays an important role in the molecular communication system. Different propagation environment and modulation techniques lead to different channel model, and most of the previous researches are mainly concentrate on the channel model in horizontal direction. However, in nature the communications between nano-machines are in short range and some of the information propagation are in the vertical direction, such as transpiration of plants, biological pump in ocean, etc. Therefore, in this paper a vertical channel model was proposed in which nano-machines communicate with each other mainly through diffusion at the vertical direction. Firstly, proposing a vertical molecular communication model, we mainly focus on the gravity, though the channel model is also affected by other main factors, such as the flow of the medium, the distance between the transmitter and the receiver, the delay or sensitivity of the transmitter and the receiver, etc. Secondly, we set up a test-bed for the vertical channel model, and verify the differences between the theoretical result and the experimental result. Finally, we get the parameters of the channel model which was proposed for the test-bed by utilizing the experimental data and the non-linear least squares method.
Copyright © 2017 Pengfei Lu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.