An Ubiquitous 2.6 GHz Radio Propagation Model for Wireless Networks Using Self-Supervised Learning From Satellite Images
The performance of any Mobile Wireless Network (MWN) is dependent on the appropriate level of radio coverage, with Path Loss (PL) models being a valuable resource for its evaluation. Recently, advancements in Machine Learning (ML) and Deep Neural Networks (DNNs) have been applied to radio propagatio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9837897/ |
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