Department of Electrical and Electronics Engineering2024-12-2920240090-677810.1109/TCOMM.2024.33817032-s2.0-85189335086https://doi.org/10.1109/TCOMM.2024.3381703https://hdl.handle.net/20.500.14288/22489Molecular Communications (MC) is a bio-inspired communication paradigm using molecules as information carriers, necessitating novel transceivers and modulation/detection techniques. In realizing practical MC receivers (MC-Rxs), biosensor field-effect transistor (bioFET)-based architectures are promising, having surface receptors that undergo reversible reactions with ligands. These interactions are converted into electrical signals via field effect, enabling the decoding of transmitted information. A significant challenge in these receivers is the limited specificity of receptors to target ligands, which leads to molecular cross-talk from similar interfering ligands co-existing in the MC channel. Decoding transmitted symbols under such interference is challenging in the time domain, especially when MC-Rx lacks prior knowledge of interferer statistics or operates near saturation. To address this, we introduce a frequency-domain detection (FDD) technique for bioFET-based MC-Rxs, which exploits the distinct binding reaction rates of different ligand types, reflected in the power spectrum of binding noise. Compared to conventional time-domain detection (TDD) technique, this method offers improved detection performance under stochastic molecular interference. We analyze the bit error probability (BEP) of FDD, confirming its superior performance in various interference scenarios. Moreover, the theoretical performance limits of FDD are validated through a particle-based spatial stochastic simulator, simulating binding reactions on MC-Rx within microfluidic channels. © 1972-2012 IEEE. Electrical engineeringElectronic engineeringTelecommunicationsJournal article1558-0857 1294594400016Q140615