Research on Spectrum Sensing Algorithm Based on Deep Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-1260-5_31
Reference16 articles.
1. Arjoune, Y., Kaabouch, N.: A comprehensive survey on spectrum sensing in cognitive radio networks: recent advances, new challenges, and future research directions. Sensors 19(1), 126 (2019)
2. Yucek, T., Arslan, H.: A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys & Tutorials 11(1), 116–130 (2009)
3. Upadhye, A., Saravanan, P., Chandra, S.S., Gurugopinath, S.: A survey on machine learning algorithms for applications in cognitive radio networks. In: 2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). pp. 01–6 (2021)
4. Awin, F., Abdel-Raheem, E., Tepe, K.: Blind spectrum sensing approaches for interweaved cognitive radio system: a tutorial and short course. IEEE Communications Surveys & Tutorials 21(1), 238–259 (2019)
5. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)
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