NDLI: A Markovian Approach to the Optimal Demodulation of Diffusion-Based Molecular Communication Networks

Content Provider	IEEE Xplore Digital Library
Author	Chun Tung Chou
Copyright Year	1972
Abstract	In a diffusion-based molecular communication network, transmitters and receivers communicate by using signalling molecules (or ligands) in a fluid medium. This paper assumes that the transmitter uses different chemical reactions to generate different emission patterns of signalling molecules to represent different transmission symbols, and the receiver consists of receptors. When the signalling molecules arrive at the receiver, they may react with the receptors to form ligand-receptor complexes. Our goal is to study the demodulation in this setup assuming that the transmitter and receiver are synchronised. We derive an optimal demodulator using the continuous history of the number of complexes at the receiver as the input to the demodulator. We do that by first deriving a communication model which includes the chemical reactions in the transmitter, diffusion in the transmission medium and the ligand-receptor process in the receiver. This model, which takes the form of a continuous-time Markov process, captures the noise in the receiver signal due to the stochastic nature of chemical reactions and diffusion. We then adopt a maximum a posteriori framework and use Bayesian filtering to derive the optimal demodulator. We use numerical examples to illustrate the properties of this optimal demodulator.
Starting Page	3728
Ending Page	3743
Page Count	16
File Size	1634834
File Format	PDF
ISSN	00906778
Volume Number	63
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Transmitters Receivers Chemicals Demodulation Molecular communication Mathematical model Biological system modeling molecular receivers Molecular communication networks modulation demodulation maximum a posteriori optimal detection stochastic models Bayesian filtering
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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