Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman
Mobile broadband (MBB) services are rapidly growing, causing a massive increase in mobile data traffic growth. This surge in data traffic is due to several factors (such as the massive increase of subscribers, mobile applications, etc.) which have led to the need for more bandwidth. Mobile service p...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-10-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016822000382 |
| _version_ | 1819284641797898240 |
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| author | Ibraheem Shayea Abdulraqeb Alhammadi Ayman A. El-Saleh Wan Haslina Hassan Hafizal Mohamad Mustafa Ergen |
| author_facet | Ibraheem Shayea Abdulraqeb Alhammadi Ayman A. El-Saleh Wan Haslina Hassan Hafizal Mohamad Mustafa Ergen |
| author_sort | Ibraheem Shayea |
| collection | DOAJ |
| description | Mobile broadband (MBB) services are rapidly growing, causing a massive increase in mobile data traffic growth. This surge in data traffic is due to several factors (such as the massive increase of subscribers, mobile applications, etc.) which have led to the need for more bandwidth. Mobile service providers are constantly improving their network efficiency by upgrading current networks and investing in newer mobile network generations. However, these improvements will not be enough to accommodate the future spectrum demands. This paper proposes a time series forecasting model to analyze future spectrum demands based on the spectrum efficiency growth of MBB networks. This model depends on two key input data: the average spectrum efficiency per site and the number of sites per technology. The model is used to predict the spectrum efficiency growth of three countries (Turkey, Malaysia, and Oman) from 2015 to 2025. The proposed model is compared with various traditional statistical models such as the Moving Average (MA), Auto-Regression (AR), Autoregressive–Moving-Average (ARMA), and Autoregressive Integrated Moving Average (ARIMA). The forecasted results indicate that the average spectrum efficiency and growth will continue to rise multiple times by 2025 compared to 2015. The data from this prediction model can be used as input data to forecast the required spectrum needed in future for any specific country. This study further contributes to the network planning of future mobile networks for Fifth Generation (5G) and Sixth Generation (6G) technology. The proposed model obtains higher accuracy (by 90%) compared to other models. The proposed model is also applicable to any country, especially when new wireless communication technologies emerge in future. It is customizable and scalable since spectrum regulators can add additional metrics that positively contribute towards accurately estimating future spectrum efficiency growth. |
| first_indexed | 2024-12-24T01:50:37Z |
| format | Article |
| id | doaj.art-00685c89318d4c77a2617c177406760c |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-12-24T01:50:37Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-00685c89318d4c77a2617c177406760c2022-12-21T17:21:44ZengElsevierAlexandria Engineering Journal1110-01682022-10-01611080518067Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and OmanIbraheem Shayea0Abdulraqeb Alhammadi1Ayman A. El-Saleh2Wan Haslina Hassan3Hafizal Mohamad4Mustafa Ergen5Electronics and Communication Engineering Department, Faculty of Electrical and Electronics Engineering, Istanbul Technical University, 34467 Sarıyer, TurkeyCommunication Systems and Networks Research Lab, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia; Corresponding author.Department of Electronics and Communication Engineering, College of Engineering, A’Sharqiyah University (ASU), Ibra 400, OmanCommunication Systems and Networks Research Lab, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, MalaysiaFaculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, MalaysiaElectronics and Communication Engineering Department, Faculty of Electrical and Electronics Engineering, Istanbul Technical University, 34467 Sarıyer, TurkeyMobile broadband (MBB) services are rapidly growing, causing a massive increase in mobile data traffic growth. This surge in data traffic is due to several factors (such as the massive increase of subscribers, mobile applications, etc.) which have led to the need for more bandwidth. Mobile service providers are constantly improving their network efficiency by upgrading current networks and investing in newer mobile network generations. However, these improvements will not be enough to accommodate the future spectrum demands. This paper proposes a time series forecasting model to analyze future spectrum demands based on the spectrum efficiency growth of MBB networks. This model depends on two key input data: the average spectrum efficiency per site and the number of sites per technology. The model is used to predict the spectrum efficiency growth of three countries (Turkey, Malaysia, and Oman) from 2015 to 2025. The proposed model is compared with various traditional statistical models such as the Moving Average (MA), Auto-Regression (AR), Autoregressive–Moving-Average (ARMA), and Autoregressive Integrated Moving Average (ARIMA). The forecasted results indicate that the average spectrum efficiency and growth will continue to rise multiple times by 2025 compared to 2015. The data from this prediction model can be used as input data to forecast the required spectrum needed in future for any specific country. This study further contributes to the network planning of future mobile networks for Fifth Generation (5G) and Sixth Generation (6G) technology. The proposed model obtains higher accuracy (by 90%) compared to other models. The proposed model is also applicable to any country, especially when new wireless communication technologies emerge in future. It is customizable and scalable since spectrum regulators can add additional metrics that positively contribute towards accurately estimating future spectrum efficiency growth.http://www.sciencedirect.com/science/article/pii/S1110016822000382Spectrum efficiency growthSpectral efficiencySpectrum forecastingMobile broadbandSpectrum demandData traffic |
| spellingShingle | Ibraheem Shayea Abdulraqeb Alhammadi Ayman A. El-Saleh Wan Haslina Hassan Hafizal Mohamad Mustafa Ergen Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman Alexandria Engineering Journal Spectrum efficiency growth Spectral efficiency Spectrum forecasting Mobile broadband Spectrum demand Data traffic |
| title | Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman |
| title_full | Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman |
| title_fullStr | Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman |
| title_full_unstemmed | Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman |
| title_short | Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman |
| title_sort | time series forecasting model of future spectrum demands for mobile broadband networks in malaysia turkey and oman |
| topic | Spectrum efficiency growth Spectral efficiency Spectrum forecasting Mobile broadband Spectrum demand Data traffic |
| url | http://www.sciencedirect.com/science/article/pii/S1110016822000382 |
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