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Closed-Loop Long-Term Experimental Molecular Communication System

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/13898879
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For the Arxiv Version of the Paper: Click hereShort Description of the Paper: In this work, we designed a biocompatible, resource-efficient, and externally controllable experimental molecular communication (MC) system. It employs the green fluorescent protein variant "Dreiklang" (GFPD) as signaling molecule, which can be reversibly switched between two fluorescent states using light of specific wavelengths. Information transmission is facilitated by an optical transmitter and an optical eraser that can write and erase information, respectively, onto the state of GFPD, while the receiver reads the encoded state through fluorescence detection. The closed-loop configuration and extended experimental durations result in unique forms of inter-symbol interference (ISI) not observed in shorter or open-loop systems. We developed a dedicated communication scheme, incorporating blind transmission start detection, symbol-by-symbol synchronization, and an adaptive threshold detection supporting higher-order modulation. Moreover, we conducted the longest MC experiment to date, both with respect to the number of bit transmitted as well as the duration of the transmission, thereby setting a novel benchmark for long-term MC experiments. Data and Code: We have published our experimental data and the Python code for synchronization and detection here on Zenodo and in an accompanying GitHub repository under the CC BY and MIT licenses, respectively. The data is shared here in two forms: i) as a zip folder containing the raw data sorted by appearance in the paper (experiment_files.zip), i.e., sorted by the paper figure numbers, ii) as a SQLite database (mmtb.db). The SQLite database can be easily integrated into the code provided on GitHub. The GitHub repository also contains step-by-step instructions on how to install the code package. Researchers are welcome to develop their own synchronization and detection schemes using our dataset. If you have any question or suggestions for improvements, feel free to contact us. Louis Wolf  Email: louis.wolf@fau.de Maike Scherer Email: maike.scherer@fau.de Lukas Brand Email: lukas.brand@fau.de Further References: This work was supported by DFG Project 290825040. For more information visit: Institute of Digital Communication, Institute of Bioprocess Engineering, Institute of Biochemistry, and Institute of Microbiology. This work is also associated to the research training group 2950: Synthetic Molecular Communication Across Different Scales: From Theory to Experiments (SyMoCADS).
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2025-02-04
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