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Molecular Communication: Modeling Noise Effects on Information Rate
Abstract
Molecular communication is a new paradigm for communication between biological nanomachines over a nano- and microscale range. As biological nanomachines (or nanomachines in short) are too small and simple to communicate through traditional communication mechanisms (e.g., through sending and receiving of radio or infrared signals), molecular communication provides a mechanism for a nanomachine (i.e., a sender) to communicate information by propagating molecules (i.e., information molecules) that represent the information to a nanomachine (i.e., a receiver). This paper describes the design of an in vitro molecular communication system and evaluates various approaches to maximize the probability of information molecules reaching a receiver(s) and the rate of information reaching the receiver(s). The approaches considered in this paper include propagating information molecules (diffusion or directional transport along protein filaments), removing excessive information molecules (natural decay or receiver removal of excessive information molecules), and encoding and decoding approaches (redundant information molecules to represent information and to decode information). Two types of molecular communication systems are considered: a unicast system in which a sender communicates with a single receiver and a broadcast system in which a sender communicates with multiple receivers. Through exploring tradeoffs among the various approaches on the two types of molecular communication systems, this paper identifies promising approaches and shows the feasibility of an in vitro molecular communication system.
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Cites
Langer, R. (1990) · Science · doi:10.1126/science.2218494 · Cited by 1,778
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
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
Kuran, M. S., Yilmaz, H. B., Tugcu, T., & Akyildiz, I. F. (2011) · 2011 IEEE International Conference on Communications (ICC) · doi:10.1109/icc.2011.5962989 · Cited by 375
Diffusion-Based Noise Analysis for Molecular Communication in Nanonetworks
Pierobon, M., & Akyildiz, I. F. (2011) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2011.2114656 · Cited by 346
Tabletop Molecular Communication: Text Messages through Chemical Signals
Farsad, N., Guo, W., & Eckford, A. W. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082935 · Cited by 269
Metadata
- Authors
- Moore, M.-J., Suda, T., & Oiwa, K.
- Venue
- IEEE Transactions on NanoBioscience
- Published
- 2009-06
- Volume
- 8
- Issue
- 2
- Pages
- 169-180
- ISSN
- 1536-1241 (ISSN-L)
- OpenAlex
- W2096552681
- Cited by
- 211
- References
- 1
- FWCI
- 10.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- Moore, M.-J., Suda, T., & Oiwa, K. (2009). Molecular Communication: Modeling Noise Effects on Information Rate. IEEE Transactions on NanoBioscience. https://doi.org/10.1109/tnb.2009.2025039
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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