- Tytuł:
- Space-Time-Frequency Machine Learning for Improved 4G/5G Energy Detection
- Autorzy:
-
Wasilewska, Małgorzata
Bogucka, Hanna - Powiązania:
- https://bibliotekanauki.pl/articles/226216.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
spectrum sensing
cognitive radio
machine learning
energy detection
4G
LTE
5G
k-nearest neighbors
random forest - Opis:
- In this paper, the future Fifth Generation (5G New Radio) radio communication system has been considered, coexisting and sharing the spectrum with the incumbent Fourth Generation (4G) Long-Term Evolution (LTE) system. The 4G signal presence is detected in order to allow for opportunistic and dynamic spectrum access of 5G users. This detection is based on known sensing methods, such as energy detection, however, it uses machine learning in the domains of space, time and frequency for sensing quality improvement. Simulation results for the considered methods: k-Nearest Neighbor sand Random Forest show that these methods significantly improves the detection probability.
- Źródło:
-
International Journal of Electronics and Telecommunications; 2020, 66, 1; 217-223
2300-1933 - Pojawia się w:
- International Journal of Electronics and Telecommunications
- Dostawca treści:
- Biblioteka Nauki
Artykuł