Modeling a Composite Molecular Communication Channel

Abstract

The paper deals with modelling of propagation medium for molecular communication, which consist of composite biological environments with multiple regions each with distinct diffusion properties for the understanding of the transport of information molecules. For this, we propose a generalized analytical approach for modelling a composite, diffusive, molecular communication channel for arbitrary placement of the transmitting and receiving nano-machines. Using this approach, we derive a generalised closed-form expression for the channel impulse response of a three dimensionally (3D) diffusive medium having multiple regions with an aim to act as a benchmark solution to validate simulations as well as to optimize the design of molecular communication systems. The pulse peak amplitude, pulse peak time and pulse width are derived to evaluate the system performance. In addition, a particle-based simulator for modelling a diffusive medium with multiple regions under three-dimensional diffusion is proposed and validated with the analytical results. It is shown that the channel impulse response and other communication metrics are significantly affected by the diffusion coefficients, regions thickness, properties of region interfaces as well as the positions of transmitter and receiver nano-machines with respect to the interfaces.

Implantable Biosensor Interface Platform for Monitoring of Atherosclerosis

“…Following the mathematical technique presented in [16,17], we derive an expression for the molecular concentration, i.e., the channel impulse response (CIR), for the multilayer MC channel. The Laplace domain expression of the molecular concentration in the i th layer can be expressed as ( ) ( ) ( )…”

Diffusion-Based Molecular Communication Channel in Presence of a Probabilistic Absorber: Single Receptor Model and Congestion Analysis

“…P (X, t) = 2 (4πDt) d/2 e −r 2 4Dt (17) in which D = δ 2 2dτ is the diffusion coefficient, d is the dimension of the diffusion environment, δ is the step length, τ is the time step, X is the Cartesian coordination of the observation point and r is the distance of observation point from origin. Please note that this is twice the actual probabiliy to match the discrete random walk analysis.…”

“…In this section, we use the probability function of particle location in an environment with no absorber, represented in (17), to develop a diffusion-based molecular channel model which consists of a probabilistic absorber.…”

“…However, in [16] the reception process is modeled using reversible ligand-receptor kinetics but the diffusion and reception processes are analyzed independently. A composite MC model is introduced in [17]. This model takes into account the issue of heterogeneity in multiple regions each with distinct diffusion properties, which can be of interest in aqueous cellular biological medium inside the human body.…”