Research Article
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6G Ağlarında Geliştirilmiş Sürdürülebilirlik ve Hücre Değişimi Yönetimi için Hücre Kapatımı

Year 2025, Volume: 9 Issue: 1, 201 - 214, 01.07.2025
https://doi.org/10.56554/jtom.1685464

Abstract

Sürdürülebilirlik ve gecikme, altıncı nesil (6G) gibi geleceğin hücresel iletişim ağları için iki kritik parametre olarak öne çıkmaktadır. Ayrıca, "bağlantısızları bağlama" girişimi — her yerde bağlantı sağlama amacı — 6G ve sonrası ağlarda hayati bir rol oynaması beklenen bir konudur. Bu bağlamda, bu çalışma söz konusu kavramların kesişim noktasında konumlanmaktadır. Daha spesifik olarak, hücre kapatma kavramlarının uygulanması yoluyla ağın enerji tüketimi en aza indirilirken, aynı zamanda devir teslim (handover) sayısı da azaltılmaktadır. Bu amaçla, karma tamsayılı programlama (MIP) tabanlı bir optimizasyon problemi modellenmiş ve sezgisel tabanlı bir çözüm algoritması geliştirilmiştir. Her yerde bağlantı hedefini desteklemek için, ağ mimarisine Uluslararası Mobil Telekomünikasyon (IMT) baz istasyonları (yani HIBS – High-Altitude Platform Station-based IMT Base Stations) olarak yüksek irtifa platform istasyonları (HAPS) entegre edilmiştir. HIBS'lerin dahil edilmesi, geniş kapsama alanları sayesinde bağlantıyı artırırken, hücre değiştirme ve trafik boşaltma amacıyla da ek kapasite sağlamaktadır. Geliştirilen optimizasyon problemi ve sezgisel çözüm algoritmasının etkinliği, farklı kullanıcılar, karasal baz istasyonları ve HIBS'lerin dahil edildiği sistem modellemeleri üzerinden gerçekleştirilen simülasyon çalışmaları ile doğrulanmıştır. Sonuçlar, önerilen metodolojinin hem enerji tüketimini hem de devir teslim sayısını etkili bir şekilde azalttığını ve performansın özellikle devir teslim cezası ve ağdaki kullanıcı sayısından önemli ölçüde etkilendiğini göstermektedir. Genel olarak bulgular, bu araştırmanın çıktılarının HIBS'lerin geniş kapsama alanı avantajı ile birlikte enerji tüketimi ve devir teslimlerin en aza indirilmesi yoluyla daha verimli ve sürdürülebilir endüstriyel operasyonlar ve yönetim sağlanmasına katkıda bulunabileceğini ortaya koymaktadır.

References

  • Abubakar, A. I., Mollel, M. S., Ozturk, M., & Ramzan, N. (2025). A secured energy saving with federated assisted modified actor-critic framework for 6G networks. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/TVT.2025.3540641
  • Abbasi, O., Yadav, A., Yanikomeroglu, H., Đào, N. -D., Senarath, G., & Zhu, P. (2024). HAPS for 6G networks: Potential use cases, open challenges, and possible solutions. IEEE Wireless Communications, 31(3), 324–331. https://doi.org/10.1109/MWC.012.2200365213
  • Banchs, A., Gutierrez-Estevez, D. M., Fuentes, M., Boldi, M., & Provvedi, S. (2019). A 5G mobile network architecture to support vertical industries. IEEE Communications Magazine, 57(12), 38–44. https://doi.org/10.1109/MCOM.001.1900258
  • Çiloğlu, B., Koç, G. B., Ozturk, M., & Yanikomeroglu, H. (2024). Cell switching in HAPS-aided networking: How the obscurity of traffic loads affects the decision. IEEE Transactions on Vehicular Technology, 73(11), 17782–17787. https://doi.org/10.1109/TVT.2024.3420245
  • Chettri, L., & Bera, R. (2020). A comprehensive survey on Internet of Things (IoT) toward 5G wireless systems. IEEE Internet of Things Journal, 7(1), 16–32. https://doi.org/10.1109/JIOT.2019.2948888 Goldsmith, A. (2005). Wireless communications. Cambridge University Press.
  • https://www.cambridge.org/core/books/wireless-communications/800BA8A8211FBECB133A7BB77CD2E2BD Gupta, A., & Jha, R. K. (2015). A survey of 5G network: Architecture and emerging technologies. IEEE Access, 3, 1206–1232. https://doi.org/10.1109/ACCESS.2015.2461602
  • Han, Z., et al. (2024). Energy consumption optimization for 5G base stations based on deep reinforcement learning. In 2024 10th International Conference on Computer and Communications (ICCC) (pp. 1625–1629). https://doi.org/10.1109/ICCC62609.2024.10942221
  • Iqbal, A., et al. (2023). Empowering non-terrestrial networks with artificial intelligence: A survey. IEEE Access, 11, 100986–101006. https://doi.org/10.1109/ACCESS.2023.3314732
  • Kement, C. E., et al. (2023). Sustaining dynamic traffic in dense urban areas with high altitude platform stations (HAPS). IEEE Communications Magazine, 61(7), 150–156. https://doi.org/10.1109/MCOM.001.2200584
  • Lin, J., Ma, M., & Wang, X. (2024). Joint design of long-term base station activation and short-term beamforming for green wireless networks. IEEE Transactions on Wireless Communications, 23(1), 185–200. https://doi.org/10.1109/TWC.2023.3276639
  • Mbarek, M. A., Meo, M., Renga, D., & Vallero, G. (2024, October). Adaptive HAPS Offloading: A Strategy for Supporting RAN During High Traffic Load. In 2024 20th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (pp. 1-6). https://doi.org/10.1109/WiMob61911.2024.10770387
  • Movahedkor, N., & Shahbazian, R. (2024). Decentralized federated deep reinforcement learning framework for energy-efficient base station switching control. In 2024 11th International Symposium on Telecommunications
  • (IST) (pp. 455–460). https://doi.org/10.1109/IST64061.2024.10843518
  • Nauman, A., Maashi, M., Alkahtani, H. K., Al-Wesabi, F. N., Aljehane, N. O., Assiri, M., ... & Khan, W. U. (2024). Efficient resource allocation and user association in NOMA-enabled vehicular-aided HetNets with high altitude platforms. Computer Communications, 216, 374-386. https://doi.org/10.1016/j.comcom.2024.01.021
  • Omid, O., Yadav, A., Yanikomeroglu, H., Đào, N. -D., Senarath, G., & Zhu, P. (2024). HAPS for 6G networks: Potential use cases, open challenges, and possible solutions. IEEE Wireless Communications, 31(3), 324–331. https://doi.org/10.1109/MWC.012.2200365
  • Ozturk, M., Salamatmoghadasi, M., & Yanikomeroglu, H. (2025). Integrating Terrestrial and Non-Terrestrial Networks for Sustainable 6G Operations: A Latency-Aware Multi-Tier Cell-Switching Approach. IEEE Network. https://doi.org/ 10.1109/MNET.2025.3554393
  • Saad, M. M., Tariq, M. A., Khan, M. T. R., & Kim, D. (2024). Non-terrestrial networks: An overview of 3GPP release 17 & 18. IEEE Internet of Things Magazine, 7(1), 20–26. https://doi.org/10.1109/IOTM.001.2300154
  • Salamatmoghadasi, M., Mehrabian, A., & Yanikomeroglu, H. (2024). Energy sustainability in dense radio access networks via high altitude platform stations. IEEE Networking Letters, 6(1), 21–25. https://doi.org/10.1109/LNET.2023.3328918
  • Song, T., Lopez, D., Meo, M., Piovesan, N., & Renga, D. (2024). High altitude platform stations: The new network energy efficiency enabler in the 6G era. In 2024 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–6). https://doi.org/10.1109/WCNC57260.2024.10571153
  • Yahya, S., & Stanica, R. (2024). Assessing the energy impact of cell switch off at an urban scale. In 2024 20th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (pp. 36–41). https://doi.org/10.1109/WiMob61911.2024.10770444

Cell switching in 6G networks for improved sustainability and handover management

Year 2025, Volume: 9 Issue: 1, 201 - 214, 01.07.2025
https://doi.org/10.56554/jtom.1685464

Abstract

Sustainability and latency are two critical parameters for future generations of cellular communication networks, such as the sixth generation (6G). Moreover, the "connecting the unconnected" initiative—enabling ubiquitous connectivity—is expected to play a vital role in 6G and beyond networks. In this regard, this work is positioned at the intersection of these concepts. More specifically, network energy consumption is minimized through the application of cell switching concepts, while simultaneously reducing the number of handovers. A mixed-integer programming (MIP) optimization problem was modelled, and a heuristic-based solution algorithm was developed. To address ubiquitous connectivity, high-altitude platform stations (HAPS) are integrated into the network architecture as IMT base stations (i.e., HIBS). The inclusion of HIBSs provides additional capacity for cell switching and traffic offloading purposes, while also enhancing connectivity through their extensive coverage footprints. The efficacy of the developed optimization problem and heuristic-based solution was validated through simulation studies, in which various users, terrestrial base stations, and HIBSs were incorporated into the system modelling. The results confirm that the proposed methodology effectively reduces both energy consumption and the number of handovers, with performance strongly influenced by the handover penalty and the number of users in the network. Overall, the findings suggest that the outcomes of this research can enable more efficient and sustainable industrial operations and management through minimized energy consumption and handovers along with the huge coverage of HIBSs.

References

  • Abubakar, A. I., Mollel, M. S., Ozturk, M., & Ramzan, N. (2025). A secured energy saving with federated assisted modified actor-critic framework for 6G networks. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/TVT.2025.3540641
  • Abbasi, O., Yadav, A., Yanikomeroglu, H., Đào, N. -D., Senarath, G., & Zhu, P. (2024). HAPS for 6G networks: Potential use cases, open challenges, and possible solutions. IEEE Wireless Communications, 31(3), 324–331. https://doi.org/10.1109/MWC.012.2200365213
  • Banchs, A., Gutierrez-Estevez, D. M., Fuentes, M., Boldi, M., & Provvedi, S. (2019). A 5G mobile network architecture to support vertical industries. IEEE Communications Magazine, 57(12), 38–44. https://doi.org/10.1109/MCOM.001.1900258
  • Çiloğlu, B., Koç, G. B., Ozturk, M., & Yanikomeroglu, H. (2024). Cell switching in HAPS-aided networking: How the obscurity of traffic loads affects the decision. IEEE Transactions on Vehicular Technology, 73(11), 17782–17787. https://doi.org/10.1109/TVT.2024.3420245
  • Chettri, L., & Bera, R. (2020). A comprehensive survey on Internet of Things (IoT) toward 5G wireless systems. IEEE Internet of Things Journal, 7(1), 16–32. https://doi.org/10.1109/JIOT.2019.2948888 Goldsmith, A. (2005). Wireless communications. Cambridge University Press.
  • https://www.cambridge.org/core/books/wireless-communications/800BA8A8211FBECB133A7BB77CD2E2BD Gupta, A., & Jha, R. K. (2015). A survey of 5G network: Architecture and emerging technologies. IEEE Access, 3, 1206–1232. https://doi.org/10.1109/ACCESS.2015.2461602
  • Han, Z., et al. (2024). Energy consumption optimization for 5G base stations based on deep reinforcement learning. In 2024 10th International Conference on Computer and Communications (ICCC) (pp. 1625–1629). https://doi.org/10.1109/ICCC62609.2024.10942221
  • Iqbal, A., et al. (2023). Empowering non-terrestrial networks with artificial intelligence: A survey. IEEE Access, 11, 100986–101006. https://doi.org/10.1109/ACCESS.2023.3314732
  • Kement, C. E., et al. (2023). Sustaining dynamic traffic in dense urban areas with high altitude platform stations (HAPS). IEEE Communications Magazine, 61(7), 150–156. https://doi.org/10.1109/MCOM.001.2200584
  • Lin, J., Ma, M., & Wang, X. (2024). Joint design of long-term base station activation and short-term beamforming for green wireless networks. IEEE Transactions on Wireless Communications, 23(1), 185–200. https://doi.org/10.1109/TWC.2023.3276639
  • Mbarek, M. A., Meo, M., Renga, D., & Vallero, G. (2024, October). Adaptive HAPS Offloading: A Strategy for Supporting RAN During High Traffic Load. In 2024 20th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (pp. 1-6). https://doi.org/10.1109/WiMob61911.2024.10770387
  • Movahedkor, N., & Shahbazian, R. (2024). Decentralized federated deep reinforcement learning framework for energy-efficient base station switching control. In 2024 11th International Symposium on Telecommunications
  • (IST) (pp. 455–460). https://doi.org/10.1109/IST64061.2024.10843518
  • Nauman, A., Maashi, M., Alkahtani, H. K., Al-Wesabi, F. N., Aljehane, N. O., Assiri, M., ... & Khan, W. U. (2024). Efficient resource allocation and user association in NOMA-enabled vehicular-aided HetNets with high altitude platforms. Computer Communications, 216, 374-386. https://doi.org/10.1016/j.comcom.2024.01.021
  • Omid, O., Yadav, A., Yanikomeroglu, H., Đào, N. -D., Senarath, G., & Zhu, P. (2024). HAPS for 6G networks: Potential use cases, open challenges, and possible solutions. IEEE Wireless Communications, 31(3), 324–331. https://doi.org/10.1109/MWC.012.2200365
  • Ozturk, M., Salamatmoghadasi, M., & Yanikomeroglu, H. (2025). Integrating Terrestrial and Non-Terrestrial Networks for Sustainable 6G Operations: A Latency-Aware Multi-Tier Cell-Switching Approach. IEEE Network. https://doi.org/ 10.1109/MNET.2025.3554393
  • Saad, M. M., Tariq, M. A., Khan, M. T. R., & Kim, D. (2024). Non-terrestrial networks: An overview of 3GPP release 17 & 18. IEEE Internet of Things Magazine, 7(1), 20–26. https://doi.org/10.1109/IOTM.001.2300154
  • Salamatmoghadasi, M., Mehrabian, A., & Yanikomeroglu, H. (2024). Energy sustainability in dense radio access networks via high altitude platform stations. IEEE Networking Letters, 6(1), 21–25. https://doi.org/10.1109/LNET.2023.3328918
  • Song, T., Lopez, D., Meo, M., Piovesan, N., & Renga, D. (2024). High altitude platform stations: The new network energy efficiency enabler in the 6G era. In 2024 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–6). https://doi.org/10.1109/WCNC57260.2024.10571153
  • Yahya, S., & Stanica, R. (2024). Assessing the energy impact of cell switch off at an urban scale. In 2024 20th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (pp. 36–41). https://doi.org/10.1109/WiMob61911.2024.10770444
There are 20 citations in total.

Details

Primary Language English
Subjects Soft Computing, Quantitative Decision Methods , Probability Theory, Applied Statistics
Journal Section Research Article
Authors

Metin Öztürk 0000-0001-8665-5291

Publication Date July 1, 2025
Submission Date April 28, 2025
Acceptance Date June 3, 2025
Published in Issue Year 2025 Volume: 9 Issue: 1

Cite

APA Öztürk, M. (2025). Cell switching in 6G networks for improved sustainability and handover management. Journal of Turkish Operations Management, 9(1), 201-214. https://doi.org/10.56554/jtom.1685464
AMA Öztürk M. Cell switching in 6G networks for improved sustainability and handover management. JTOM. July 2025;9(1):201-214. doi:10.56554/jtom.1685464
Chicago Öztürk, Metin. “Cell Switching in 6G Networks for Improved Sustainability and Handover Management”. Journal of Turkish Operations Management 9, no. 1 (July 2025): 201-14. https://doi.org/10.56554/jtom.1685464.
EndNote Öztürk M (July 1, 2025) Cell switching in 6G networks for improved sustainability and handover management. Journal of Turkish Operations Management 9 1 201–214.
IEEE M. Öztürk, “Cell switching in 6G networks for improved sustainability and handover management”, JTOM, vol. 9, no. 1, pp. 201–214, 2025, doi: 10.56554/jtom.1685464.
ISNAD Öztürk, Metin. “Cell Switching in 6G Networks for Improved Sustainability and Handover Management”. Journal of Turkish Operations Management 9/1 (July 2025), 201-214. https://doi.org/10.56554/jtom.1685464.
JAMA Öztürk M. Cell switching in 6G networks for improved sustainability and handover management. JTOM. 2025;9:201–214.
MLA Öztürk, Metin. “Cell Switching in 6G Networks for Improved Sustainability and Handover Management”. Journal of Turkish Operations Management, vol. 9, no. 1, 2025, pp. 201-14, doi:10.56554/jtom.1685464.
Vancouver Öztürk M. Cell switching in 6G networks for improved sustainability and handover management. JTOM. 2025;9(1):201-14.

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