Transfer Function Models for Molecular Communication Channels

• Applicants: Professor Dr.-Ing. Rudolf Rabenstein; Professor Dr.-Ing. Robert Schober
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2019 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 430166206

Molecular communication (MC) is an emerging field of research at the intersection of science and engineering. MC is the prevalent means of communication in natural biological systems, e.g. between a presynaptic neuron and a postsynaptic neuron in the synaptic cleft or between bacteria during quorum sensing. Engineered MC systems are expected to enable communication between nanomachines (synthetic or biological objects whose components are at nanometer scale) and to facilitate interaction with biological systems. In MC, information is encoded in the properties (e.g. concentration, time of release, type) of small particles such as molecules or ions. The development of the underlying communication and information theory and corresponding testbeds for experimental verification are still in their infancy. In this context, powerful and flexible analytical models and fast simulation methods for the spatio-temporal distribution of the information-carrying particles (i.e., their concentration as a function of space and time) are of paramount importance. On the one hand, such models and methods are needed for the communication- and information-theoretical design and analysis of MC systems, and on the other hand, they are needed to guide the development of (often very expensive) experiments. Unfortunately, the existing analytical models for MC systems are restricted to very simple MC channels, often relying on unrealistic simplifying assumptions (e.g. unbounded environment, point source transmitter, transparent receiver), and the existing simulation methods are either accurate but slow (e.g. particle based methods) or fast but not insightful (e.g. numerical solvers for partial differential equations), i.e., they do not offer any insight into the impact of the various MC channel parameters (e.g. boundary and initial conditions, chemical reaction rates). Therefore, in this project, we will develop powerful and flexible analytical models for the spatio-temporal distribution of the information-carrying particles in MC systems based on a transfer function approach, which provides insight into the impact of the parameters of the MC system and lends itself to fast numerical evaluation. The expected outcomes of this project will include (1) a novel framework for analytical modelling of MC systems based on transfer functions, (2) transfer function models (TFMs) for four important example MC systems, (3) a communication-theoretical characterization of these example MC systems based on the TFMs, (4) methods for parameter estimation in MC channels based on TFMs, and (5) a software library for the simulation and evaluation of MC systems based on TFMs.

• DFG Programme: Research Grants