Extended master equation models for molecular communication networks

TL;DR

This paper introduces RDMEX, a stochastic reaction-diffusion master equation model for molecular communication networks, enabling analysis of multiple transmitters and receivers with linear reaction kinetics.

Contribution

The paper develops RDMEX, a novel stochastic modeling framework for molecular communication networks that accounts for multiple transmitters and receivers using master equations.

Findings

RDMEX can model multiple transmitters and receivers.

Closed-form expressions for receiver output mean are derived.

Receiver signals are influenced by other receivers' presence.

Abstract

We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signalling molecules, which are diffused over the medium, to the receiver to realise 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 signalling molecule counts, while diffusion in the medium and chemical reactions at the receivers are modelled 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.