Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency
The 5th generation of mobile communications, currently being rolled out, aims to improve network performance and efficiency over the older generations. With mmWaves, densified cell deployment is necessary for 5G networks, increasing capacity and improving network coverage. This imposes a considerabl...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10129880/ |
| _version_ | 1797813922704654336 |
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| author | Macoumba Fall Younes Balboul Mohammed Fattah Said Mazer Moulhime El Bekkali Ahmed D. Kora |
| author_facet | Macoumba Fall Younes Balboul Mohammed Fattah Said Mazer Moulhime El Bekkali Ahmed D. Kora |
| author_sort | Macoumba Fall |
| collection | DOAJ |
| description | The 5th generation of mobile communications, currently being rolled out, aims to improve network performance and efficiency over the older generations. With mmWaves, densified cell deployment is necessary for 5G networks, increasing capacity and improving network coverage. This imposes a considerable increase in the energy consumption of the 5G stations, which not only increases operating expenses for operators but also burdens the environment. Optimizing the energy consumption of 5G networks would be necessary to curb the energy curve. In this context, this paper presents a new algorithm called Energy Consumption Optimization Algorithm (ECOA), which combines cell selection and standby techniques to optimize energy consumption while preserving network performance. A comparison is conducted between ECOA and standard cell selection modes to evaluate the performance of the conventional approach. Our algorithm exhibits good performance, particularly in high-density, high-load scenarios. For instance, in a site with 25 Pico base stations serving 500 users, our algorithm achieves an average throughput of 23 Mb/s per user while consuming 1750.75 W of energy. This represents a 2.44% increase in energy consumption compared to the optimal solution. |
| first_indexed | 2024-03-13T07:59:50Z |
| format | Article |
| id | doaj.art-251f7e4254a5440aadc383fae6b13df9 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T07:59:50Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-251f7e4254a5440aadc383fae6b13df92023-06-01T23:00:24ZengIEEEIEEE Access2169-35362023-01-0111507945080410.1109/ACCESS.2023.327820910129880Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy EfficiencyMacoumba Fall0https://orcid.org/0000-0001-9469-7010Younes Balboul1https://orcid.org/0000-0002-7521-9141Mohammed Fattah2https://orcid.org/0000-0001-6128-9715Said Mazer3https://orcid.org/0000-0003-4812-7708Moulhime El Bekkali4https://orcid.org/0000-0002-1098-6841Ahmed D. Kora5https://orcid.org/0000-0002-7636-2054IASSE Laboratory, Sidi Mohamed Ben Abdellah University, Fez, MoroccoIASSE Laboratory, Sidi Mohamed Ben Abdellah University, Fez, MoroccoIMAGE Laboratory, Moulay Ismail University, Meknes, MoroccoIASSE Laboratory, Sidi Mohamed Ben Abdellah University, Fez, MoroccoIASSE Laboratory, Sidi Mohamed Ben Abdellah University, Fez, MoroccoEDMI, Cheikh Anta Diop University, Dakar, SenegalThe 5th generation of mobile communications, currently being rolled out, aims to improve network performance and efficiency over the older generations. With mmWaves, densified cell deployment is necessary for 5G networks, increasing capacity and improving network coverage. This imposes a considerable increase in the energy consumption of the 5G stations, which not only increases operating expenses for operators but also burdens the environment. Optimizing the energy consumption of 5G networks would be necessary to curb the energy curve. In this context, this paper presents a new algorithm called Energy Consumption Optimization Algorithm (ECOA), which combines cell selection and standby techniques to optimize energy consumption while preserving network performance. A comparison is conducted between ECOA and standard cell selection modes to evaluate the performance of the conventional approach. Our algorithm exhibits good performance, particularly in high-density, high-load scenarios. For instance, in a site with 25 Pico base stations serving 500 users, our algorithm achieves an average throughput of 23 Mb/s per user while consuming 1750.75 W of energy. This represents a 2.44% increase in energy consumption compared to the optimal solution.https://ieeexplore.ieee.org/document/10129880/5Gcell selectionecologyenergy consumptionenergy efficiencyhetnet |
| spellingShingle | Macoumba Fall Younes Balboul Mohammed Fattah Said Mazer Moulhime El Bekkali Ahmed D. Kora Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency IEEE Access 5G cell selection ecology energy consumption energy efficiency hetnet |
| title | Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency |
| title_full | Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency |
| title_fullStr | Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency |
| title_full_unstemmed | Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency |
| title_short | Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency |
| title_sort | towards sustainable 5g networks a proposed coordination solution for macro and pico cells to optimize energy efficiency |
| topic | 5G cell selection ecology energy consumption energy efficiency hetnet |
| url | https://ieeexplore.ieee.org/document/10129880/ |
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