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Publikationen

Seite 4 von 6.

  1. Deep Learning for Fading Channel Prediction

    In: IEEE Open Journal of the Communications Society, Vol. 1, Pages 320-332, IEEE, 3/2020.

  2. Long-Range Fading Channel Prediction Using Recurrent Neural Network

    In: IEEE Consumer Communications and Networking Conference. IEEE Consumer Communications and Networking Conference (CCNC-2020), January 10-13, Las …

  3. Recurrent Neural Networks with Long Short-Term Memory for Fading Channel Prediction

    In: 2020 IEEE 91st Vehicular Technology Conference. IEEE Vehicular Technology Conference (VTC-2020), May 25-28, Antwerp, Belgium, IEEE, 2020.

  4. A Deep Learning Method to Predict Fading Channel in Multi-Antenna Systems

    In: 2020 IEEE 91st Vehicular Technology Conference. IEEE Vehicular Technology Conference (VTC-2020), May 25-28, Antwerp, Belgium, IEEE, 2020.

  5. Implementation of OpenAirInterface-based real-world channel measurement for evaluating wireless transmission algorithms

    Workshop on Next Generation Networks and Applications (NGNA-2020), December 14-18, Kaiserslautern, Germany, TU Kaiserslautern, 2020.

  6. Neural Network-Based Fading Channel Prediction: A Comprehensive Overview

    In: IEEE Access, Vol. 7, No. 1, Pages 118112-118124, IEEE, 8/2019.

  7. Recurrent Neural Network-based Frequency-Domain Channel Prediction for Wideband Communications

    In: Proceedings of Vehicular Technology Conference. IEEE Vehicular Technology Conference (VTC-2019), 2019 IEEE 89th (Spring), April 28 - May 1, Kuala …

  8. A Comparison of Wireless Channel Predictors: Artificial Intelligence versus Kalman Filter

    In: Proceedings of IEEE ICC. IEEE International Conference on Communications (ICC-2019), May 20-24, Shanghai, China, IEEE, 2019.