Eike-Manuel Edelmann, M.Sc.

Eike-Manuel Edelmann, M.Sc.

Forschungsgebiete

  • Untersuchung neuromorpher Hardware und Entwicklung entsprechender Algorithmen im Kontext der Nachrichtentechnik
  • Ressourcenzuweisung im Mobilfunk mittels Deep Reinforcement Learning

Lehre

  • Übung Nachrichtentechnik I (seit WS 20/21)
  • Praktikum Nachrichtentechnik (seit SS 20)

Aktuelle Arbeiten

Abschlussarbeiten

Offene Abschlussarbeiten

Titel Betreuer Art
Ressourcenzuweisung mittels Spiking Neural Network-basierten Deep Reinforcement Learning Algorithmen Eike-Manuel Edelmann MA

Laufende Abschlussarbeiten

Titel Betreuer Art

Derzeit gibt es keine laufenden Abschlussarbeiten.

Gesamte Liste der Veröffentlichungen

Zeitschriftenbeiträge

  1. A. von Bank, E.-M. Edelmann, S. Miao, J. Mandelbaum and L. Schmalen, "Spiking neural belief propagation decoder for short block length LDPC codes," IEEE Commun. Lett., 2024, https://arxiv.org/abs/2410.11543
    [ Zitieren ]  [ Code ]

Konferenzbeiträge

  1. L. Schmalen, V. Lauinger, J. Ney, N. Wehn, P. Matalla, S. Randel, A. von Bank and E. M. Edelmann, "Recent advances on machine learning-aided DSP for short-reach and long-haul optical communications," Proc. Opt. Fiber Commun. Conf. (OFC), San Francisco, CA, USA, Mar. 2025, invited presentation
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  2. A. von Bank, E.-M. Edelmann, J. Mandelbaum and L. Schmalen, "Spiking neural belief propagation decoder for LDPC codes with small variable node degrees," Proc. Intl. ITG Conf. on Systems, Communications, and Coding (SCC), Karlsruhe, Germany, Mar. 2025, https://arxiv.org/abs/2412.15897
    [ Zitieren ]  
  3. A. von Bank, E. Edelmann and L. Schmalen, "Energy-efficient spiking neural network equalization for IM/DD systems with optimized neural encoding," Proc. Opt. Fiber Commun. Conf. (OFC), San Diego, CA, USA, Mar. 2024, https://arxiv.org/abs/2312.12909
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  4. A. von Bank, E. Edelmann and L. Schmalen, "Spiking neural network decision feedback equalization for IM/DD systems," Proc. Advanced Photonic Congress: Signal Processing in Photonic Communications (SPPCom), Busan, South Korea, Jul. 2023, https://arxiv.org/abs/2304.14152
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  5. E. M. Bansbach, A. von Bank and L. Schmalen, "Spiking neural network decision feedback equalization," Proc. Intl. Workshop on Smart Antennas and ITG Conf. on Systems, Communications, and Coding (WSA-SCC), Braunschweig, Germany, Feb. 2023, https://arxiv.org/abs/2211.04756
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  6. E. M. Bansbach, Y. Kiyak and L. Schmalen, "Deep reinforcement learning for uplink multi-carrier non-orthogonal multiple access resource allocation using buffer state information," Proc. European Wireless, Dresden, Germany, Sep. 2022, https://arxiv.org/abs/2208.14689
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  7. E. M. Bansbach, V. Eliachevitch and L. Schmalen, "Deep reinforcement learning for wireless resource allocation using buffer state information," Proc. IEEE Global Commun. Conf. (GLOBECOM), Madrid, Spain, Dec. 2021, preprint available at https://arxiv.org/abs/2108.12198
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