Performance evaluation of machine learning methods for path loss prediction in rural environment at 3.7 GHz
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s11276-021-02682-3.pdf
Reference42 articles.
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2. El Khaled, Z., Ajib, W., & Mcheik, H. (2020). An accurate empirical path loss model for heterogeneous fixed wireless networks below 5.8 GHz frequencies. IEEE Access, 8, 182755–182775.
3. Thrane, J., Zibar, D., & Christiansen, H. L. (2020). Model-aided deep learning method for path loss prediction in mobile communication systems at 2.6 GHz. IEEE Access, 8, 7925–7936.
4. Popoola, S. I., Misra, S., & Atayero, A. A. (2018). Outdoor path loss predictions based on extreme learning machine. Wireless Personal Communications, 99(1), 441–460.
5. Moraitis, N., Vouyioukas, D., Gkioni, A., & Louvros, S. (2020). Measurements and path loss models for a TD-LTE network at 3.7 GHz in rural areas. Wireless Networks, 26(4), 2891–2904.
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