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Normal inverse Gaussian approximation for arrival time difference in flow-induced molecular communications
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Haselmayr, Werner, Efrosinin, Dmitry and Guo, Weisi (2018) Normal inverse Gaussian approximation for arrival time difference in flow-induced molecular communications. IEEE Transactions on Molecular, Biological and Multiscale Communications, 3 (4). pp. 259-264. doi:10.1109/tmbmc.2018.2887237
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Official URL: https://doi.org/10.1109/tmbmc.2018.2887237
Abstract
The inverse Gaussian (IG) distribution is a well- established distribution for the first hitting time in flow-induced diffusion molecular communications. However, the distribution of the difference between two independent IG-distributed random variables has not been derived yet, although it is very important for the analysis of many molecular communication systems. For example, for deriving crossover probabilities or characterizing the noise in time between release modulation. In this letter, we propose an approximation by a normal inverse Gaussian (NIG) distribution and derive an asymptotic tail approximation. Numerical evaluations showed that the NIG approximation matches very well with the solution obtained through numerical integration, in particular for the tails. Moreover, the asymptotic tail approximation converges very quickly to the actual probability and outperforms state-of-the-art tail approximations.
| Item Type: | Journal Article | ||||||||
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| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
| Library of Congress Subject Headings (LCSH): | Molecular communication (Telecommunication), Gaussian distribution | ||||||||
| Journal or Publication Title: | IEEE Transactions on Molecular, Biological and Multiscale Communications | ||||||||
| Publisher: | IEEE | ||||||||
| ISSN: | 2332-7804 | ||||||||
| Official Date: | 1 December 2018 | ||||||||
| Dates: |
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| Volume: | 3 | ||||||||
| Number: | 4 | ||||||||
| Page Range: | pp. 259-264 | ||||||||
| DOI: | 10.1109/tmbmc.2018.2887237 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| Related URLs: | |||||||||
| Open Access Version: |
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