2020/12/31 by Murat Kuşcu, Kuscu, Murat, Özgür B. Akan +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · Engineering · #Advanced biosensing and bioanalysis techniques #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #Molecular Communication and Nanonetworks
paper · pdf · doi:10.48550/arxiv.2101.00081
openalex publication_date 2020/12/31 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Molecular Communications (MC) is a bio-inspired communication technique that\nuses molecules to transfer information among bio-nano devices. In this paper,\nwe focus on the detection problem for biological MC receivers employing ligand\nreceptors to infer the transmitted messages encoded into the concentration of\nmolecules, i.e., ligands. In practice, receptors are not ideally selective\nagainst target ligands, and in physiological environments, they can interact\nwith multiple types of ligands at different reaction rates depending on their\nbinding affinity. This molecular cross-talk can cause a substantial\ninterference on MC. Here we consider a particular scenario, where there is\nnon-negligible concentration of interferer molecules in the channel, which have\nsimilar receptor-binding characteristics with the information molecules, and\nthe receiver employs single type of receptors. We investigate the performance\nof four different detection methods, which make use of different statistics of\nthe ligand-receptor binding reactions: instantaneous number of bound receptors,\nunbound time durations of receptors, bound time durations of receptors, and\ncombination of unbound and bound time durations of receptors within a sampling\ntime interval. The performance of the introduced detection methods are\nevaluated in terms of bit error probability for varying strength of molecular\ninterference, similarity between information and interferer molecules, number\nof receptors, and received concentration difference between bit-0 and bit-1\ntransmissions. We propose synthetic receptor designs that can convert the\nrequired receptor statistics to the concentration of intracellular molecules,\nand chemical reaction networks that can chemically perform the computations\nrequired for detection.\n