Arrival Modeling and Error Analysis for Molecular Communication via Diffusion with Drift

Abstract

The arrival of molecules in molecular communication via diffusion (MCvD) is a counting process and exhibits binomial distribution by its nature. Even if the arrival of molecules is described well by the binomial process, the binomial cumulative distribution function (CDF) is difficult to work with when considering consecutively sent symbols. Therefore, in the literature, Poisson and Gaussian approximations of the binomial distribution are used. In this paper, we analyze these two approximations of the binomial model of the arrival process in MCvD with drift. We investigate the regions in which either Poisson or Gaussian model is better in terms of root mean squared error (RMSE) of the CDFs with varying the distance, drift velocity, and the number of emitted molecules. Moreover, we confirm the boundaries of the region via numerical simulations and derive the error probabilities for continuous communication and analyze which model approximates it more accurately.