This paper considers a diffusion-based molecular communication system, where the transmitter uses reaction shift keying (RSK) as the modulation scheme. We focus on the demodulation of RSK signal at the receiver. The receiver consists of a front-end molecular circuit and a back-end demodulator. The front-end molecular circuit is a set of chemical reactions consisting of multiple chemical species. The optimal demodulator computes the posteriori probability of the transmitted symbols given the history of the observation. The derivation of the optimal demodulator requires the solution to a specific Bayesian filtering problem. The solution to this Bayesian filtering problem had been derived for a few specific molecular circuits and specific choice(s) of observed chemical species. The derivation of such solution is also lengthy. The key contribution of this paper is to present a general solution to this Bayesian filtering problem, which can be applied to any molecular circuit and any choice of observed species.
An alternative way of designing receivers for molecular communication is by using molecular circuits, see @cite_28 @cite_46 for example. Various aspects of receiver molecular circuits have been studied in the literature. We will discuss two aspects here: capacity and noise properties. The information transmission capacity of a number of types of linear receiver molecular circuits is compared in @cite_28 . The capacity analysis for molecular communication based on ligand receptor binding has been presented in @cite_14 @cite_2 . The capacity of these systems in the continuous-time is presented in @cite_10 . The noise properties of ligand-receptor binding type of receivers is studied in @cite_7 @cite_32 . All the above papers assume that the receiver is a ligand-receptor binding process with only two reactions: binding and unbinding. However, in this paper, we propose a methodology that can be used for any molecular circuit.
@cite_14 @cite_7 @cite_28 @cite_32 @cite_2 @cite_46 @cite_10
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A diffusion-based molecular communication system has two major components: the diffusion in the medium, and the ligand-reception. Information bits, encoded in the time variations of the concentration of molecules, are conveyed to the receiver front through the molecular diffusion in the medium. The receiver, in turn, measures the concentration of the molecules in its vicinity in order to retrieve the information. This is done via ligand-reception process. In this paper, we develop models to study the constraints imposed by the concentration sensing at the receiver side and derive the maximum rate by which a ligand-receiver can receive information. Therefore, the overall capacity of the diffusion channel with the ligand receptors can be obtained by combining the results presented in this paper with our previous work on the achievable information rate of molecular communication over the diffusion channel. Molecular Communication (MC), i.e., the exchange of information through the emission, propagation, and reception of molecules, is a promising paradigm for the interconnection of autonomous nanoscale devices, known as nanomachines. Synthetic biology techniques, and in particular the engineering of biological circuits, are enabling research towards the programming of functions within biological cells, thus paving the way for the realization of biological nanomachines. The design of MC systems built upon biological circuits is particularly interesting since cells naturally employ the MC paradigm in their interactions, and possess many of the elements required to realize this type of communication. This paper focuses on the identification and systems-theoretic modeling of a minimal subset of biological circuit elements necessary to be included in an MC system design where the message-bearing molecules are propagated via free diffusion between two cells. The system-theoretic models are here detailed in terms of transfer functions, from which analytical expressions are derived for the attenuation and the delay experienced by an information signal through the MC system. Numerical results are presented to evaluate the attenuation and delay expressions as functions of realistic biological parameters. We consider diffusion-based molecular communication networks where the receivers consist of a set of chemical reactions or a molecular circuit. At the receivers of these networks, the signalling molecules react with the molecular circuit to produce output molecules. The counts of output molecules over time is the output signal of the receiver. The aim of this paper is to investigate the impact of different molecular circuits on the noise properties and information transmission capacity of molecular communication networks. In particular, we show that some molecular circuits have lower noise and higher information transmission capacity. 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. In diffusion-based molecular communications, messages can be conveyed via the variation in the concentration of molecules in the medium. In this paper, we intend to analyze the achievable capacity in transmission of information from one node to another in a diffusion channel. We observe that because of the molecular diffusion in the medium, the channel possesses memory. We then model the memory of the channel by a two-step Markov chain and obtain the equations describing the capacity of the diffusion channel. By performing a numerical analysis, we obtain the maximum achievable rate for different levels of the transmitter power, i.e., the molecule production rate. Molecular communication networks can be used to realise communication between nanoscale devices. In a molecular communication network, transmitters and receivers communicate by using signalling molecules. At the receivers, the signalling molecules react, via a chain of chemical reactions, to produce output molecules. The counts of output molecules over time is the output signal of the receiver. The output signal is noisy due to the stochastic nature of diffusion and chemical reactions. This paper aims to characterise the properties of the output signal. We do this by modelling the transmission medium, transmitter and receiver. In order to simplify the analysis, we model the transmitter as a sequence which specifies the number of molecules emitted by the transmitter over time. This paper considers two receiver reaction mechanisms, reversible conversion and linear catalytic, which can be used to approximate, respectively, ligand-receptor binding and enzymatic reactions. These two mechanisms are chosen because, if we consider them on their own (i.e. without the transmitter and diffusion), the ordinary differential equations describing the mean behaviour of these two reaction mechanisms have the same form; however, if we consider the end-to-end behaviour from the transmitter signal to the mean variance of the number of output molecules, then these two receiver reaction mechanisms have very different behaviours. We show this by deriving analytical expressions for the mean, variance and frequency properties of the number of output molecules of these two receiver reaction mechanisms. In addition, for reversible conversion, we are able to derive the exact probability distribution of the number of output molecules. Our model allows us to study the impact of design parameters on the communication performance. For example, we assume that our receiver is enclosed by a membrane and we study the impact of the diffusibility of molecules across this membrane on the communication performance. 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.