Performance Analysis of a Deep Neural Network-Based Spectrum Sensing Approach
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49413-0_60
Reference14 articles.
1. Alwis, C.D., et al.: Survey on 6G frontiers: trends, applications, requirements, technologies and future research. IEEE Open J. Commun. Soc. 2, 836–886 (2021)
2. Syed, S.N., et al.: Deep learning approaches for spectrum sensing in cognitive radio networks. In: 2022 25th International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 480–485, Herning, Denmark, 2022
3. Ahmed, Q.Z., Hafeez, M., Khan, F.A., Lazaridis, P.: Towards beyond 5G future wireless networks with focus towards indoor localization. In: 2020 IEEE Eighth International Conference on Communications and Networking (ComNet), Hammamet, Tunisia, 2020, pp. 1–5
4. Solanki, S., Dehalwar, V., Choudhary, J.: Deep learning for spectrum sensing in cognitive radio. Symmetry 13(1), 147 (2021)
5. 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)
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