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3D stochastic geometry model for large-scale molecular communication systems
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Deng, Yansha, Noel, Adam, Guo, Weisi, Nallanathan, Arumugam and Elkashlan, Maged (2017) 3D stochastic geometry model for large-scale molecular communication systems. In: IEEE Global Communications Conference (GLOBECOM 2016), Washington, USA, 04-08 Dec 2016. Published in: 2016 IEEE Global Communications Conference (GLOBECOM) ISBN 9781509013289.
An open access version can be found in:
Official URL: http://doi.org/10.1109/GLOCOM.2016.7841486
Abstract
Information delivery using chemical molecules is an integral part of biology at multiple distance scales and has attracted recent interest in bioengineering and communication. The collective signal strength at the receiver (i.e., the expected number of observed molecules inside the receiver), resulting from a large number of transmitters at random distances (e.g., due to mobility), can have a major impact on the reliability and efficiency of the molecular communication system. Modeling the collective signal from multiple diffusion sources can be computationally and analytically challenging. In this paper, we present the first tractable analytical model for the collective signal strength due to randomly-placed transmitters, whose positions are modelled as a homogeneous Poisson point process in three-dimensional (3D) space. By applying stochastic geometry, we derive analytical expressions for the expected number of observed molecules and the signal-to-interference ratios (SIRs) at a fully absorbing receiver and a passive receiver. Our results reveal that the collective signal strength at both types of receivers increases proportionally with increasing transmitter density. The SIR of a fully absorbing receiver is greater than that of a passive receiver, which suggests greater reliability at the fully absorbing receiver. The proposed framework dramatically simplifies the analysis of large-scale molecular systems in both communication and biological applications.
| Item Type: | Conference Item (Paper) | ||||||
|---|---|---|---|---|---|---|---|
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
| Journal or Publication Title: | 2016 IEEE Global Communications Conference (GLOBECOM) | ||||||
| Publisher: | IEEE | ||||||
| ISBN: | 9781509013289 | ||||||
| Official Date: | 6 February 2017 | ||||||
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| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | IEEE Global Communications Conference (GLOBECOM 2016) | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Washington, USA | ||||||
| Date(s) of Event: | 04-08 Dec 2016 | ||||||
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| Open Access Version: |
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