The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Improving Receiver Performance of Diffusive Molecular Communication With Enzymes
Open accessAbstract
This paper studies the mitigation of intersymbol interference in a diffusive molecular communication system using enzymes that freely diffuse in the propagation environment. The enzymes form reaction intermediates with information molecules and then degrade them so that they cannot interfere with future transmissions. A lower bound expression on the expected number of molecules measured at the receiver is derived. A simple binary receiver detection scheme is proposed where the number of observed molecules is sampled at the time when the maximum number of molecules is expected. Insight is also provided into the selection of an appropriate bit interval. The expected bit error probability is derived as a function of the current and all previously transmitted bits. Simulation results show the accuracy of the bit error probability expression and the improvement in communication performance by having active enzymes present.
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Cites
Stochastic Simulation of Chemical Kinetics
Gillespie, D. T. (2007) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.58.032806.104637 · Cited by 2,115
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Stochastic simulation of chemical reactions with spatial resolution and single molecule detail
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Molecular Communication in Fluid Media: The Additive Inverse Gaussian Noise Channel
Srinivas, K. V., Eckford, A. W., & Adve, R. S. (2012) · IEEE Transactions on Information Theory · doi:10.1109/tit.2012.2193554 · Cited by 391
Modulation Techniques for Communication via Diffusion in Nanonetworks
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Cellular concentrations of enzymes and their substrates
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Capacity of a Diffusion-Based Molecular Communication System With Channel Memory and Molecular Noise
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Energy model for communication via diffusion in nanonetworks
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Cited by
A Comprehensive Survey of Recent Advancements in Molecular Communication
Farsad, N., Yilmaz, H. B., Eckford, A., Chae, C.-B., & Guo, W. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2527741 · Cited by 968
Channel Modeling for Diffusive Molecular Communication—A Tutorial Review
Jamali, V., Ahmadzadeh, A., Wicke, W., Noel, A., & Schober, R. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2919455 · Cited by 357
Self-citationReceiver Design in Molecular Communications: An Approach Based on Artificial Neural Networks
Qian, X., & Di Renzo, M. (2018) · 2018 15th International Symposium on Wireless Communication Systems (ISWCS) · doi:10.1109/iswcs.2018.8491088 · Cited by 26
Metadata
- Authors
- Noel, A., Cheung, K. C., & Schober, R.
- Venue
- IEEE Transactions on NanoBioscience
- Published
- 2014-03
- Volume
- 13
- Issue
- 1
- Pages
- 31-43
- ISSN
- 1536-1241 (ISSN-L)
- 1558-2639
- OpenAlex
- W2059488492
- Cited by
- 261
- References
- 24
- FWCI
- 14.57
- Type
- journal article
- Language
- en
- Open access
- green
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- Noel, A., Cheung, K. C., & Schober, R. (2014). Improving Receiver Performance of Diffusive Molecular Communication With Enzymes. IEEE Transactions on NanoBioscience. https://doi.org/10.1109/tnb.2013.2295546
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
