Literature Database Entry

debus2024reinforcement

Lisa Y. Debus, Pit Hofmann, Jorge Torres Gómez, Frank H. P. Fitzek and Falko Dressler, "Reinforcement Learning-based Receiver for Molecular Communication with Mobility," Proceedings of VDE Workshop Biosignals, Göttingen, Germany, February 2024.

Abstract

Research in molecular communication (MC) is moving forward in big steps, enabling next-generation communication between nanosensors and presenting an alternative communication model for applications in life sciences and other industrial applications. While a lot of the current research in investigates the setup and en-/decoding process in these testbeds, few tackle the problem of inherently mobile structures with ever-changing channel characteristics and achieving symbol synchronization under these circumstances. In this paper, we employ reinforcement learning (RL) to present an approach to this problem. Using data from a real-world macroscale testbed, we train an RL agent to detect synchronization sequences via threshold adaption in a mobile setting. We comparatively evaluate our approach with the state of the art and report the RL agents ability to adapt to changing channel behavior produced by mobility, achieving a low probability of missed detection and small misalignment with the symbol time.

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Lisa Y. Debus
Pit Hofmann
Jorge Torres Gómez
Frank H. P. Fitzek
Falko Dressler

BibTeX reference

@inproceedings{debus2024reinforcement,
    author = {Debus, Lisa Y. and Hofmann, Pit and Torres G{\'{o}}mez, Jorge and Fitzek, Frank H. P. and Dressler, Falko},
    title = {{Reinforcement Learning-based Receiver for Molecular Communication with Mobility}},
    publisher = {VDE},
    address = {G{\"{o}}ttingen, Germany},
    booktitle = {VDE Workshop Biosignals},
    month = {2},
    year = {2024},
   }
   
   

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Last modified: 2024-04-29