Diffusion-based noise analysis for molecular communication in nanonetworks

Molecular communication (MC) is a promising bio-inspired paradigm, in which molecules are used to encode, transmit and receive information at the nanoscale. Very limited research has addressed the problem of modeling and analyzing the MC in nanonetworks. One of the main challenges in MC is the proper study and characterization of the noise sources. The objective of this paper is the analysis of the noise sources in diffusion-based MC using tools from signal processing, statistics and communication engineering. The reference diffusion-based MC system for this analysis is the physical end-to-end model introduced in a previous work by the same authors. The particle sampling noise and the particle counting noise are analyzed as the most relevant diffusion-based noise sources. The analysis of each noise source results in two types of models, namely, the physical model and the stochastic model. The physical model mathematically expresses the processes underlying the physics of the noise source. The stochastic model captures the noise source behavior through statistical parameters. The physical model results in block schemes, while the stochastic model results in the characterization of the noises using random processes. Simulations are conducted to evaluate the capability of the stochastic model to express the diffusion-based noise sources represented by the physical model.