We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signaling molecules, which are diffused over the medium, to the receiver to realize the communication. In order to be able to engineer synthetic molecular communication networks, mathematical models for these networks are required. This paper proposes a new stochastic model for molecular communication networks called reaction-diffusion master equation with exogenous input (RDMEX). The key idea behind RDMEX is to model the transmitters as time series of signaling molecule counts, while diffusion in the medium and chemical reactions at the receivers are modeled as Markov processes using master equation. An advantage of RDMEX is that it can readily be used to model molecular communication networks with multiple transmitters and receivers. For the case where the reaction kinetics at the receivers is linear, we show how RDMEX can be used to determine the mean and covariance of the receiver output signals, and derive closed-form expressions for the mean receiver output signal of the RDMEX model. These closed-form expressions reveal that the output signal of a receiver can be affected by the presence of other receivers. Numerical examples are provided to demonstrate the properties of the model.
Molecular communication networks can be divided into two categories, according to whether they are natural or synthetic. Natural molecular communication networks are prevalent in living organisms. Their synthetic counterparts, though still rare, do exist. For example, @cite_29 presents a system with multiple genetically engineered cells that use cell signalling to coordinate their behaviour. The modelling of natural and synthetic molecular communication networks is studied in different disciplines. The former is mainly studied in biophysics and mathematical physiology, while the latter in synthetic biology. There is also a recent interest in the engineering community to study molecular communication networks from a communication theory point of view @cite_4 @cite_27 @cite_31 . This gives rise to a new research area called nano communication networks @cite_26 .
@cite_26 @cite_4 @cite_29 @cite_27 @cite_31
2018036523 2059089080 2005822392 2143177102
The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, we present the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. We then discuss challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications. 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. This article presents a branch of research where the use of molecules to encode and transmit information among nanoscale devices (nanomachines) is investigated as a bio-inspired viable solution to realize nano-communication networks. Unlike traditional technologies, molecular communication is a radically new paradigm, which demands novel solutions, including the identification of naturally existing molecular communication mechanisms, the establishment of the foundations of a molecular information theory, or the development of architectures and networking protocols for nanomachines. The tight connection of this cutting edge engineering research field with biology will ultimately enable both the bio-inspired study of molecular nanonetwork architectures and their realization with tools already available in nature. The testbed described in this article, which is based on a microfluidic device hosting intercommunicating populations of genetically engineered bacteria, is a clear example of this research direction. Abstract Recent advances in synthetic biology, in particular towards the engineering of DNA-based circuits, are providing tools to program man-designed functions within biological cells, thus paving the way for the realization of biological nanoscale devices, known as nanomachines. By stemming from the way biological cells communicate in the nature, Molecular Communication (MC), i.e., the exchange of information through the emission, propagation, and reception of molecules, has been identified as the key paradigm to interconnect these biological nanomachines into nanoscale networks, or nanonetwork. The design of MC nanonetworks built upon biological circuits is particularly interesting since cells possess many of the elements required to realize this type of communication, thus enabling the design of cooperative functions in the biological environment. In this paper, a systems-theoretic modeling is realized by analyzing a minimal subset of biological circuit elements necessary to be included in an MC nanonetwork design where the message-bearing molecules are propagated via free diffusion between two cells. The obtained system-theoretic models stem from the biochemical processes underlying cell-to-cell MC, and are analytically characterized by their transfer functions, attenuation and delay experienced by an information signal exchanged by the communicating cells. Numerical results are presented to evaluate the obtained analytical expressions as functions of realistic biological parameters.