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.
The capacity of molecular communications based on ligand-receptor binding has been studied in @cite_20 @cite_3 assuming discrete samples of the number of complexes are available. A recent work @cite_15 considers the capacity of such systems in the continuous-time limit. Instead of focusing on the capacity, our work focuses on demodulation.
@cite_15 @cite_3 @cite_20
1996262444 2125863473 1991545742 2115084976
We model the ligand-receptor molecular communication channel with a discrete-time Markov model, and show how to obtain the capacity of this channel. We show that the capacity-achieving input distribution is iid; further, unusually for a channel with memory, we show that feedback does not increase the capacity of this channel. Molecular communication (MC) will enable the exchange of information among nanoscale devices. In this novel bio-inspired communication paradigm, molecules are employed to encode, transmit and receive information. In the most general case, these molecules are propagated in the medium by means of free diffusion. An information theoretical analysis of diffusion-based MC is required to better understand the potential of this novel communication mechanism. The study and the modeling of the noise sources is of utmost importance for this analysis. The objective of this paper is to provide a mathematical study of the noise at the reception of the molecular information in a diffusion-based MC system when the ligand-binding reception is employed. The reference diffusion-based MC system for this analysis is the physical end-to-end model introduced in a previous work by the same authors, where the reception process is realized through ligand-binding chemical receptors. The reception noise is modeled in this paper by following two different approaches, namely, through the ligand-receptor kinetics and through the stochastic chemical kinetics. The ligand-receptor kinetics allows to simulate the random perturbations in the chemical processes of the reception, while the stochastic chemical kinetics provides the tools to derive a closed-form solution to the modeling of the reception noise. The ligand-receptor kinetics model is expressed through a block scheme, while the stochastic chemical kinetics results in the characterization of the reception noise using stochastic differential equations. Numerical results are provided to demonstrate that the analytical formulation of the reception noise in terms of stochastic chemical kinetics is compliant with the reception noise behavior resulting from the ligand-receptor kinetics simulations. Abstract In this paper, a strength-based optimum signal detection scheme for binary concentration-encoded molecular communication (CEMC) system has been presented. In CEMC, a single type of information molecule is assumed to carry the information from the transmitting nanomachine (TN), through the propagation medium, to the receiving nanomachine (RN) in the form of received concentration of information molecules at the location of the RN. We consider a pair of nanomachines communicating by means of on–off keying (OOK) transmission protocol in a three-dimensional ideal (i.e. free) diffusion-based unbounded propagation environment. First, based on stochastic chemical kinetics of the reaction events between ligand molecules and receptors, we develop a mathematical receiver model of strength-based detection scheme for OOK CEMC system. Using an analytical approach, we explain the receiver operating characteristic (ROC) curves of the receiver thus developed. Finally, we propose a variable threshold -based detection scheme and explain its communication range and rate dependent characteristics. We show that it provides an improvement in the communication ranges compared to fixed threshold -based detection scheme. (Part of this paper has been peer-reviewed and published in BWCCA-2012 conference in Victoria, BC, 12–14 November, 2012 [20] .) 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.