Maximum Likelihood Detection With Ligand Receptors for Diffusion-Based Molecular Communications in Internet of Bio-Nano Things.
IEEE transactions on nanobioscience
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Kuscu, M., & Akan, O. (2018). Maximum Likelihood Detection With Ligand Receptors for Diffusion-Based Molecular Communications in Internet of Bio-Nano Things.. IEEE transactions on nanobioscience, 17 (1), 44-54. https://doi.org/10.1109/tnb.2018.2792434
Molecular Communication (MC) is a bio-inspired communication technique that uses molecules as a method of information transfer among nanoscale devices. MC receiver is an essential component having profound impact on the communication system performance. However, the interaction of the receiver with information bearing molecules has been usually oversimplified in modeling the reception process and developing signal detection techniques. In this paper, we focus on the signal detection problem of MC receivers employing receptor molecules to infer the transmitted messages encoded into the concentration of molecules, i.e., ligands. Exploiting the observable characteristics of ligand-receptor binding reaction, we first introduce a Maximum Likelihood (ML) detection method based on instantaneous receptor occupation ratio, as aligned with the current MC literature. Then, we propose a novel ML detection technique, which exploits the amount of time the receptors stay unbound in an observation time window. A comprehensive analysis is carried out to compare the performance of the detectors in terms of bit error probability. In evaluating the detection performance, emphasis is given to the receptor saturation problem resulting from the accumulation of messenger molecules at the receiver as a consequence of intersymbol interference. The results reveal that detection based on receptor unbound time is quite reliable even in saturation, whereas the reliability of detection based on receptor occupation ratio substantially decreases as the receiver gets saturated. Finally, we also discuss the potential methods of implementing the detectors.
Ligands, Biotechnology, Diffusion, Nanotechnology, Models, Biological, Internet, Computers, Molecular
European Commission FP7 ERC Consolidator Grant (616922)
European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (665564)
External DOI: https://doi.org/10.1109/tnb.2018.2792434
This record's URL: https://www.repository.cam.ac.uk/handle/1810/287022