Path Loss Model Predictions for Different Gsm Networks in the UNN Campus Environment for Estimation of Propagation loss

Different path loss models have been predicted for different locations. Nevertheless, none of these models can be regarded as a superior model, because environmental factors play a vital role in the path loss of every environment. In this paper, signal attenuation prediction models for Global System for Mobile Communication (GSM) networks in the University of Nigeria, Nsukka for four different networks namely Airtel, Globacom, Mobile Telecommunication Network (MTN), and 9mobile networks were proposed. Field measurements based on the signal strength and path loss of GSM operating at 1800MHz were carried out for the development of the proposed attenuation model, in the area for the four GSM networks. The measured data for signal strength and path loss were used to develop the models. To formulate the proposed attenuation models for the considered networks in the area, the data collected during field measurements were analyzed using linear regression analysis. The proposed models were compared with the measured and four popular standard attenuation models such as Hata, Cost 231-Hata, SUI, and ECC-33. The path loss for the standard empirical models was gotten from simulation using a standard MATLAB 2016b package. The results showed that the proposed attenuation models performed better than all the considered models

based on its least error value.

Overall Rating

0

5 Star
(0)
4 Star
(0)
3 Star
(0)
2 Star
(0)
1 Star
(0)
APA

S.Enyi1, V , U., V , Ugwu3, F & Ogbonna4, C (2023). Path Loss Model Predictions for Different Gsm Networks in the UNN Campus Environment for Estimation of Propagation loss. Afribary. Retrieved from https://track.afribary.com/works/path-loss-model-predictions-for-different-gsm-networks-in-the-unn-campus-environment-for-estimation-of-propagation-loss

MLA 8th

S.Enyi1, Valentine et. al. "Path Loss Model Predictions for Different Gsm Networks in the UNN Campus Environment for Estimation of Propagation loss" Afribary. Afribary, 12 Jul. 2023, https://track.afribary.com/works/path-loss-model-predictions-for-different-gsm-networks-in-the-unn-campus-environment-for-estimation-of-propagation-loss. Accessed 25 Dec. 2024.

MLA7

S.Enyi1, Valentine, Val U. , Felix Ugwu3 and Chidubem Ogbonna4 . "Path Loss Model Predictions for Different Gsm Networks in the UNN Campus Environment for Estimation of Propagation loss". Afribary, Afribary, 12 Jul. 2023. Web. 25 Dec. 2024. < https://track.afribary.com/works/path-loss-model-predictions-for-different-gsm-networks-in-the-unn-campus-environment-for-estimation-of-propagation-loss >.

Chicago

S.Enyi1, Valentine , U., Val , Ugwu3, Felix and Ogbonna4, Chidubem . "Path Loss Model Predictions for Different Gsm Networks in the UNN Campus Environment for Estimation of Propagation loss" Afribary (2023). Accessed December 25, 2024. https://track.afribary.com/works/path-loss-model-predictions-for-different-gsm-networks-in-the-unn-campus-environment-for-estimation-of-propagation-loss