Capacity of a Binary Droplet-Based Microfluidic Channel with Memory and Anticipation for Flow-Induced Molecular Communications

Flow-induced Molecular Communications are a promising communication paradigm based on the exchange of molecule concentrations in a continuous fluid, guided and directed through microfluidic pipes. An emerging approach to implement this type of communications is based on discrete (or droplet-based) microfluidics. It exploits the idea to represent binary information by encapsulating the signaling molecules inside droplets which are dispersed in an immiscible fluid and delivered, through micro pipes, to the destination. The objective of this work is to study a binary droplet-based microfluidic system for flow-induced molecular communications from an information theoretical perspective. To this end, we first show that the binary discrete microfluidic channel is characterized by memory and anticipation. Accordingly, we provide a mathematical model based on a finite-state Markov chain. Finally, we evaluate the capacity of the binary droplet-based microfluidic channel.