Modelling 1D Partially Absorbing Boundaries for Brownian Molecular Communication Channels
Molecular Communication (MC) architectures suffer from molecular build-up in the channel if they do not have appropriate reuptake mechanisms. The molecular build-up either leads to intersymbol interference (ISI) or reduces the transmission rate. To measure the molecular build-up, we derive analytic expressions for the incidence rate and absorption rate for one-dimensional MC channels where molecular dispersion obeys the Brownian Motion. We verify each of our key results with Monte Carlo simulations. Our results contribute to the development of more complicated models and analytic expressions to measure the molecular build-up and the impact of ISI in MC.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Mixed analytical-stochastic simulation method for the recovery of a Brownian gradient source from probability fluxes to small windows
Is it possible to recover the position of a source from the steady-state fluxes of Brownian particles to small absorbing windows located on the boundary of a domain? To address this question, we develop a numerical proce…
PositionSaliency Detection via Bidirectional Absorbing Markov Chain
Traditional saliency detection via Markov chain only considers boundaries nodes. However, in addition to boundaries cues, background prior and foreground prior cues play a complementary role to enhance saliency detection…
Saliency DetectionSuperpixelsPrice modelling under generalized fractional Brownian motion
The Generalized fractional Brownian motion (gfBm) is a stochastic process that acts as a generalization for both fractional, sub-fractional, and standard Brownian motion. Here we study its use as the main driver for pric…
LEMMADiffusive Molecular Communication in a Biological Spherical Environment with Partially Absorbing Boundary
Diffusive molecular communication (DMC) is envisioned as a promising approach to help realize healthcare applications within bounded biological environments. In this paper, a DMC system within a biological spherical envi…
Reaction coordinate flows for model reduction of molecular kinetics
In this work, we introduce a flow based machine learning approach, called reaction coordinate (RC) flow, for discovery of low-dimensional kinetic models of molecular systems. The RC flow utilizes a normalizing flow to de…