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Using Deep Learning and Radio Virtualisation for Efficient Spectrum Sharing Among Coexisting Networks.

, , , , , and . CrownCom, volume 261 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 165-174. Springer, (2018)

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Signal Processing for Temporal Spectrum Sharing in a Multi-Radar Environment., , , and . IEEE Trans. Cogn. Commun. Netw., 3 (2): 123-137 (2017)Radio Access Technology Characterisation Through Object Detection., , , and . CoRR, (2020)Context-aware radar modeling framework., , , , and . DySPAN, page 113-122. IEEE, (2015)Using Deep Learning and Radio Virtualisation for Efficient Spectrum Sharing Among Coexisting Networks., , , , , and . CrownCom, volume 261 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 165-174. Springer, (2018)Shared Spectrum Monitoring Using Deep Learning., , , and . IEEE Trans. Cogn. Commun. Netw., 7 (4): 1171-1185 (2021)DySPAN Spectrum Challenge: Situational Awareness and Opportunistic Spectrum Access Benchmarked., , , , , , , , and . IEEE Trans. Cogn. Commun. Netw., 3 (3): 550-562 (2017)Radio Access Technology characterisation through object detection., , , and . Comput. Commun., (2021)An alternative implementation of a cyclostationary detector., , , and . WPMC, page 45-49. IEEE, (2012)Reduction of radar band exclusion zones through database-aided beamforming., , , and . DySPAN, page 309-318. IEEE, (2015)Implementation of temporal spectrum sharing for radar bands., , , , , and . DySPAN, page 271-272. IEEE, (2015)