Journal
PROCEEDINGS OF THE IEEE
Volume 107, Issue 7, Pages 1256-1301Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JPROC.2019.2919455
Keywords
Diffusion; end-to-end channel impulse response (CIR); experiment-driven models; flow; molecular communications (MCs); reaction; simulation-driven models; statistical model
Categories
Funding
- German Research Foundation [SCHO 831/7-1, SCHO 831/11-1]
- Friedrich-Alexander-Universitat Erlangen-Nurnberg through the Emerging Fields Initiative
- STAEDTLER Foundation
- Federal Ministry of Education and Research (BMBF) under Project MAMOKO
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Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications, such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide the channel models for time-varying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate the simulation- and experiment-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems.
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