Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "prediction model" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Characterization of Propagation Models at 5G Network and Effects of SAR on Human Brain
Autorzy:
Al-Aamri, Nawal
Nadir, Zia
Bait-Suwailam, Mohammed
Al-Lawati, Hassan
Powiązania:
https://bibliotekanauki.pl/articles/2074140.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
pathloss
prediction
5G
RMSE
CI model
ABG model
SAR
Opis:
Nowadays, the world is turning into technology, fast internet and high signal quality. To ensure high signal quality, the network planners have to predict the pathloss and signal strength of the transmitted signal at specific distances in the design stage. The aim of this research is to provide a generalized pathloss model to suit the urban area in Muscat Governorate in the Sultanate of Oman. The research covers 5G network pathloss in the Muttrah Business District (MBD) area. It includes Close In (CI) model and Alpha Beta Gamma (ABG) model with 3.45GHz. The results of 5G models were compared with real experimental data in MBD by calculating Root Mean Square Error RMSE. Other cells at MBD area were used for reverification. To validate the modified pathloss models of 5G, they were applied at different cells in Alkhoud area. Furthermore, this paper also deals the effect of Specific Absorption Rate (SAR) on the human brain for ensuring safety due to close proximity to cell towers. The SAR values were calculated indirectly from the electric field strength of different antennas. Calculated results were compared with the international standards defined limits on the human brain.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 2; 343--349
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Characterization of Propagation Models in Wireless Communications for 4G Network
Autorzy:
Al-Aamri, Nawal
Nadir, Zia
Al-Lawati, Hassan
Suwailam, Mohammed Bait
Powiązania:
https://bibliotekanauki.pl/articles/2055256.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
path loss model
prediction
4G
RMSE
Opis:
Estimating the pathloss and signal strength of the transmitted signal at specific distances is one of the main objectives of network designers. This paper aims to provide generalized pathloss models appropriate for urban areas in Muscat the capital city of the Sultanate of Oman environment. The research includes studying different models of pathloss for the 4G cellular network at Muttrah Business District (MBD) at Muscat. Different models (Free Space model, Okumura Hata, Extended Sakagami, Cost231 Hata, ECC-33 Hata – Okumura extended, Ericsson, Egli, and SUI) are used with 800MHz. The results of the prediction models are compared with real measured data by calculating RMSE. The generalized models are created by modified original models to get accepted RMSE values. Different cells at MBD are tested by modified models. The RMSE values are then calculated for verification purposes. To validate the modified pathloss models of 4G, they are also applied at different cells in a different city in the capital. It has approximately the same environment as MBD. The modified pathloss models provided accepted predictions in new locations.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 1; 137--143
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies