Literature Database Entry

debus2024decoding

Lisa Y. Debus, "Decoding Media Modulation Sharply: A Reinforcement Learning-based Receiver," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2024. (Advisor: Jorge Torres Gómez; Referees: Falko Dressler and Robert Schober)

Abstract

Molecular communication (MC) is the next-generation communication technology that offers new pathways for modern technology in life sciences and industrial applications. Multiple techniques have been proposed on how to design MC receivers, assuming synchronous operation and perfect timing during the decoding process. This assumption only holds in theoretical discussions of the topic, though. Communication in real-world systems necessitates dedicated synchronization between the communication partners. Solving the problem of synchronization analytically is challenging in free diffusion-based MC channels but becomes even more complex in the case of a real testbed with changing channel parameters. Instead, in this thesis, we tackle this problem by the application of machine learning (ML) and present a reinforcement learning (RL)-based synchronizer for a media modulation (MM) MC testbed. The developed RL agent continually adapts a decoding threshold which it uses to detect transmitted synchronization frames. We comparatively evaluate the RL synchronizer’s true positive rate (TPR), false positive rate (FPR), and symbol time offset (STO) performance versus two different synchronization methods in the context of changing testbed characteristics. Our results exhibit the potential of our RL-based approach to synchronization with a comparatively high detection accuracy. We additionally discuss the possibility of extending it to function reliably in more dynamic MC channels.

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Lisa Y. Debus

BibTeX reference

@phdthesis{debus2024decoding,
    author = {Debus, Lisa Y.},
    title = {{Decoding Media Modulation Sharply: A Reinforcement Learning-based Receiver}},
    advisor = {Torres G{\'{o}}mez, Jorge},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {3},
    referee = {Dressler, Falko and Schober, Robert},
    school = {TU Berlin (TUB)},
    type = {Master's Thesis},
    year = {2024},
   }
   
   

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Last modified: 2024-10-14