A Markov Chain Channel Model for Active Transport Molecular Communication
In molecular communication, small particles such as molecules are used to convey information. These particles are released by a transmitter into a fluidic environment, where they propagate freely (e.g. through diffusion) or through externals means (e.g. different types of active transport) until they arrive at the receiver. Although there are a number of different mathematical models for the diffusion-based molecular communication, active transport molecular communication (ATMC) lacks the necessary theoretical framework. Previous works had to rely almost entirely on full Monte Carlo simulations of these systems. However, full simulations can be time consuming because of the computational complexities involved. In this paper, a Markov channel model has been presented, which could be used to reduce the amount of simulations necessary for studying ATMC without sacrificing accuracy. Moreover, a mathematical formula for calculating the transition probabilities in the Markov chain model is derived to complete our analytical framework. Comparing our proposed models with full simulations, it is shown that these models can be used to calculate parameters such channel capacity accurately in a timely manner.