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.
The interest of research community in molecular communication is on the rise as shown by recent surveys @cite_38 @cite_15 @cite_21 @cite_27 @cite_30 .
@cite_30 @cite_38 @cite_21 @cite_27 @cite_15
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Abstract Molecular communication enables nanomachines to exchange information with each other by emitting molecules to their surrounding environment. Molecular nanonetworks are envisioned as a number of nanomachines that are deployed in an environment to share specific molecular information such as odor, flavor, or any chemical state. In this paper, using the stochastic model of molecular reactions in biochemical systems, a realistic channel model is first introduced for molecular communication. Then, based on the realistic channel model, we introduce a deterministic capacity expression for point-to-point, broadcast, and multiple-access molecular channels. We also investigate information flow capacity in a molecular nanonetwork for the realization of efficient communication and networking techniques for frontier nanonetwork applications. The results reveal that molecular point-to-point, broadcast, and multiple-access channels are feasible with a satisfactorily high molecular communication rate, which allows molecular information flow in nanonetworks. Furthermore, the derived molecular channel model with input-dependent noise term also reveals that unlike a traditional Gaussian communication channel, achievable capacity is affected by both lower and upper bounds of the channel input in molecular communication channels. Molecular communication is a new nano-scale communication paradigm that enables nanomachines to communicate with each other by emitting molecules to their surrounding environment. Nanonetworks are also envisioned to be composed of a number of nanomachines with molecular communication capability that are deployed in an environment to share specific molecular information such as odor, flavour, light, or any chemical state. In this paper, using the principles of natural ligand-receptor binding mechanisms in biology, we first derive a capacity expression for single molecular channel in which a single Transmitter Nanomachine (TN) communicates with a single Receiver Nanomachine (RN). Then, we investigate the capacity of the molecular multiple-access channel in which multiple TNs communicate with a single RN. Numerical results reveal that high molecular communication capacities can be attainable for the single and multiple-access molecular channels. Abstract Molecular communication networks consist of transmitters and receivers distributed in a fluid medium. The communication in these networks is realised by the transmitters emitting signalling molecules, which are diffused in the medium to reach the receivers. This paper investigates the properties of noise, or the variance of the receiver output, in molecular communication networks. The noise in these networks come from multiple sources: stochastic emission of signalling molecules by the transmitters, diffusion in the fluid medium and stochastic reaction kinetics at the receivers. We model these stochastic fluctuations by using an extension of the master equation. We show that, under certain conditions, the receiver outputs of linear molecular communication networks are Poisson distributed. The derivation also shows that noise in these networks is a nonlinear function of the network parameters and is non-additive. Numerical examples are provided to illustrate the properties of this type of Poisson channels. Abstract Molecular communication uses molecules (i.e., biochemical signals) as an information medium and allows biologically and artificially created nano- or microscale entities to communicate over a short distance. It is a new communication paradigm; it is different from the traditional communication paradigm, which uses electromagnetic waves (i.e., electronic and optical signals) as an information medium. Key research challenges in molecular communication include design of system components (i.e., a sender, a molecular propagation system, a receiver, and a molecular communication interface) and mathematical modeling of each system component as well as entire systems. We review all research activities in molecular communication to date, from its origin to recent experimental studies and theoretical approaches for each system component. As a model molecular communication system, we describe an integrated system that combines a molecular communication interface (using a lipid vesicle embedded with channel-forming proteins), a molecular propagation system (using microtubule motility on kinesin molecular motors and DNA hybridization), and a sender receiver (using giant lipid vesicles embedded with gemini-peptide lipids). We also present potential applications and the future outlook of molecular communication.