This repository contains the dataset for the paper L. Bonati, S. D'Oro, M. Polese, S. Basagni, and T. Melodia, "Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks", IEEE Communications Magazine, vol. 59, no. 10, pp. 21–27, October 2021. Please cite the paper if you plan to use it in your publication. [dataset]
This repository contains the dataset for the paper D. Uvaydov, S. D’Oro, F. Restuccia and T. Melodia, "DeepSense: Fast Wideband Spectrum Sensing Through Real-Time In-the-Loop Deep Learning", IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, 2021. [dataset]
This repository contains the dataset for the paper L. Baldesi, F. Restuccia and T. Melodia, "ChARM: NextG Spectrum Sharing Through Data-Driven Real-Time O-RAN Dynamic Control", IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, 2022. [dataset]
This repository contains the dataset for the paper A. Al-Shawabka, P. Pietraski, S. B Pattar, F. Restuccia, and T. Melodia, "DeepLoRa: Fingerprinting LoRa Devices at Scale Through Deep Learning and Data Augmentation", ACM MobiHoc 2021 - ACM Intl. Symp. on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, 2021. [dataset]
This repository contains the dataset for the paper A. Al-Shawabka, F. Restuccia, S. D'Oro, T. Jian, B. Costa Rendon, N. Soltani, J. Dy, K. Chowdhury, S. Ioannidis and T. Melodia, "Exposing the Fingerprint: Dissecting the Impact of the Wireless Channel on Radio Fingerprinting", IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, 2020. [dataset] [details]
L. Bonati, S. D'Oro, M. Polese, S. Basagni, and T. Melodia, "Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks", IEEE Communications Magazine, vol. 59, no. 10, pp. 21–27, October 2021. [pdf] [bibtex]
M. Polese, L. Bertizzolo, L. Bonati, A. Gosain, and T. Melodia, "An Experimental mmWave Channel Model for UAV-to-UAV Communications," in Proc. of ACM Workshop on Millimeter-Wave Networks and Sensing Systems (mmNets), London, UK, Sep. 2020. arXiv:2007.11869 [cs.NI] [bibtex] [video] [dataset]
D. Uvaydov, S. D’Oro, F. Restuccia and T. Melodia, "DeepSense: Fast Wideband Spectrum Sensing Through Real-Time In-the-Loop Deep Learning", IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, 2021. [pdf] [bibtex] [dataset]
L. Baldesi, F. Restuccia and T. Melodia, "ChARM: NextG Spectrum Sharing Through Data-Driven Real-Time O-RAN Dynamic Control", IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, 2021. Best Paper Award [pdf] [bibtex] [dataset]
A. Al-Shawabka, P. Pietraski, S. B Pattar, F. Restuccia, and T. Melodia, "DeepLoRa: Fingerprinting LoRa Devices at Scale Through Deep Learning and Data Augmentation," to appear in Proc. of ACM Intl. Symp. on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), October 2021. [pdf] [bibtex] [dataset]
A. Al-Shawabka, F. Restuccia, S. D'Oro, T. Jian, B. Costa Rendon, N. Soltani, J. Dy, K. Chowdhury, S. Ioannidis and T. Melodia, "Exposing the Fingerprint: Dissecting the Impact of the Wireless Channel on Radio Fingerprinting," Proc. of IEEE Intl. Conference on Computer Communications (IEEE INFOCOM), Jul. 2020 (AR: 20%). [pdf] [bibtex] [dataset] [details]