Frequency-Domain Detection for Molecular Communication with Cross-Reactive Receptors

TL;DR

This paper introduces a frequency-domain detection method for bioFET-based molecular communication receivers that leverages differences in ligand-receptor reaction rates to mitigate molecular cross-talk and improve decoding accuracy.

Contribution

It proposes a novel frequency-domain detection technique that exploits reaction rate differences to enhance molecular communication receiver performance under interference.

Findings

FDD outperforms TDD in decoding accuracy under interference.

Analytical BEP bounds are validated through stochastic simulations.

FDD effectively mitigates molecular cross-talk in bioFET-based MC receivers.

Abstract

Molecular Communications (MC) is a bio-inspired communication paradigm that uses molecules as information carriers, requiring unconventional transceivers and modulation/detection techniques. Practical MC receivers (MC-Rxs) can be implemented using field-effect transistor biosensor (bioFET) architectures, where surface receptors reversibly react with ligands. The time-varying concentration of ligand-bound receptors is translated into electrical signals via field effect, which is used to decode the transmitted information. However, ligand-receptor interactions do not provide an ideal molecular selectivity, as similar ligand types, i.e., interferers, co-existing in the MC channel, can interact with the same type of receptors. Overcoming this molecular cross-talk in the time domain can be challenging, especially when Rx has no knowledge of the interferer statistics or operates near saturation. Therefore, we propose a frequency-domain detection (FDD) technique for bioFET-based MC-Rxs that exploits the difference in binding reaction rates of different ligand types reflected in the power spectrum of the ligand-receptor binding noise. We derive the bit error probability (BEP) of the FDD technique and demonstrate its effectiveness in decoding transmitted concentration signals under stochastic molecular interference compared to a widely used time-domain detection (TDD) technique. We then verified the analytical performance bounds of the FDD through a particle-based spatial stochastic simulator simulating reactions on the MC-Rx in microfluidic channels.