Linearity of Sequential Molecular Signals in Turbulent Diffusion Channels

Molecular communication underpins biological system coordination across multiple spatial and temporal scales. Whilst significant research has focused on micro-scale diffusion dominated channels, far less is understood of macro-scale flow dominated channels. The latter introduces complex fluid dynamic forces, one of which is turbulent diffusion. Molecular Communication via Turbulent Diffusion (MCvTD) more accurately reflects realistic molecular channels in both pheromone signaling and chemical engineering. Current literature assumes linear combining between sequential molecular signals, but this assumption may not hold when turbulence is introduced. Here, we use computational fluid dynamics (CFD) simulation to show that sequential MCvTD signals do indeed linearly combine. This is a non-trivial and non-intuitive result and our conclusion allows the research field to leverage on existing linear combining signal analysis. To ensure robustness of our results, we test for the received signal strength and Inter-Symbol-Interference (ISI) under different concentrations, co-flow rate, and the information sequence. Also, we introduce a basis for the channel model in a way that for any k sequential signals in which k ≥ 4, by understanding the 1 ≤ k ≤ 3 signals and the last signal, we can represent the other signals. We expect these results to be useful to both molecular communication and biological signaling researchers.