Deep Learning Classification of 3.5 GHz Band Spectrograms with
Applications to Spectrum Sensing

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Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing

19 June 2018

Adam Wunderlich

Peter J. Jeavons

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Papers citing "Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing"

11 / 11 papers shown

Title
Jamming Attacks on Decentralized Federated Learning in General Multi-Hop Wireless NetworksConference on Computer Communications Workshops (INFOCOM), 2023 Yi Shi Y. Sagduyu T. Erpek AAML 271 6 0 12 Jan 2023
Sensing-Throughput Tradeoffs with Generative Adversarial Networks for NextG Spectrum SharingIEEE Military Communications Conference (MILCOM), 2022 Yi Shi Y. Sagduyu 151 1 0 27 Dec 2022
Adversarial Machine Learning and Defense Game for NextG Signal Classification with Deep LearningIEEE Military Communications Conference (MILCOM), 2022 Y. Sagduyu AAML 101 2 0 22 Dec 2022
Blind Estimation of a Doubly Selective OFDM Channel: A Deep Learning Algorithm and Theory T. Getu N. Golmie D. Griffith 160 2 0 30 May 2022
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks Yi Shi Y. Sagduyu T. Erpek FedML 161 19 0 06 Apr 2022
A Novel Capsule Neural Network Based Model for Drowsiness Detection Using Electroencephalography SignalsExpert systems with applications (ESWA), 2022 Luis Guarda Juan Tapia E. Droguett M. Ramos 71 37 0 04 Apr 2022
Design of an Novel Spectrum Sensing Scheme Based on Long Short-Term Memory and Experimental ValidationInternational Journal of Communications (JC), 2021 Nupur Choudhury K. K. Sarma C. Kalita Aradhana Misra 130 4 0 21 Nov 2021
Adversarial Machine Learning for 5G Communications Security Y. Sagduyu T. Erpek Yi Shi AAML 185 48 0 07 Jan 2021
Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network SlicingIEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (MDCLN), 2020 Yi Shi Y. Sagduyu T. Erpek 147 64 0 14 Sep 2020
Spectrum Sensing and Signal Identification with Deep Learning based on Spectral Correlation Function Kürşat Tekbıyık Özkan Akbunar A. R. Ekti Ali̇ Görçi̇n Gunes Karabulut Kurt Khalid A. Qaraqe 132 3 0 17 Mar 2020
Spectrum Sensing Based on Deep Learning Classification for Cognitive RadiosChina Communications (CC), 2019 Shilian Zheng Shichuan Chen Peihan Qi Huaji Zhou Xiaoniu Yang 73 134 0 13 Sep 2019