Biological Optical-to-Chemical Signal Conversion Interface: A Small-scale Modulator for Molecular Communications

TL;DR

An analytical parametric model is developed for the induced chemical signal as a function of the applied optical signal and a training-based channel estimator is derived that estimates the parameters of the proposed model to fit the measurement data based on a least square error approach.

Abstract

Although many exciting applications of molecular communication (MC) systems are envisioned to be at microscale, the MC testbeds reported so far are mostly at macroscale. To link the macroworld to the microworld, we propose and demonstrate a biological signal conversion interface that can also be seen as a microscale modulator. In particular, the proposed interface transduces an optical signal, which is controlled using an LED, into a chemical signal by changing the pH of the environment. The modulator is realized using E. coli bacteria as microscale entity expressing the light-driven proton pump gloeorhodopsin from Gloeobacter violaceus. Upon inducing external light stimuli, these bacteria locally change their surrounding pH level by exporting protons into the environment. To verify the effectiveness of the proposed optical-to-chemical signal converter, we analyze the pH signal measured by a pH sensor, which serves as receiver. We develop an analytical parametric model for the induced chemical signal as a function of the applied optical signal. Using this model, we derive a training-based channel estimator which estimates the parameters of the proposed model to fit the measurement data. We further derive the optimal maximum likelihood detector and a suboptimal low-complexity detector to recover the transmitted data from the measured received signal. It is shown that the proposed parametric model is in good agreement with the measurement data. Moreover, for an example scenario, we show that the proposed setup is able to successfully convert an optical signal representing a sequence of binary symbols into a chemical signal with a bit rate of 1 bit/minute and recover the transmitted data from the chemical signal using the proposed estimation and detection~schemes. The proposed modulator may form the basis for future MC testbeds and applications at microscale.

Figures (7)

• Figure 1: Biological modulator model. (a) Benchtop experimental setup; (b) Schematic illustration.
• Figure 2: The light-driven proton pump bacteriorhodopsin. (a) Biological function of bacteriorhodopsin in a native cell; (b) Schematic transmission model.
• Figure 3: a) Optical signal; b) Measured proton concentration $c(t)$ and analytical signal $\bar{c}(t)$ vs. time.
• Figure 4: a) Optical signal corresponding to symbol sequence $[10011000101011101101]$; b) Measured proton concentration $c(t)$ and analytical signal $\bar{c}(t)$ vs. time. The dashed lines represent the start of a new symbol interval.
• Figure 5: Normalized histograms of the random fluctuation component $e(t)$ of two different measurements and the corresponding fitted normal probability density functions (PDFs).

Theorems & Definitions (2)

• Remark 1
• Remark 2