[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
research-article

AI-Driven Optimization of Small Cell Deployment for Beyond 5G Networks

Published: 01 January 2024 Publication History

Abstract

The focus of this study is to examine how Artificial Intelligence (AI) influences the deployment of resources in the context of Beyond 5G (B5G) communications for modern applications. Employing a range of machine learning techniques, including neural networks and graph-based approaches, the investigation utilizes a small cell open dataset from the United States. The results highlight the exceptional performance of neural network models in streamlining small cell deployment, a pivotal aspect for improving both Internet of Things (IoT) connectivity and efficiency across expansive networks and critical applications. The study’s insights are relevant for telecommunications professionals and policymakers, offering practical perspectives on the transformative impact of AI in B5G scenarios within highly connected information systems.

References

[1]
Al-Turjman, R, Ever, E., Zahmatkesh, H., 2019. Small cells in the forthcoming 5g/iot: Traffic modelling and deployment overview. IEEE Communications Surveys and Tutorials 21, 28-65.
[2]
Alsharif, M.H., Kelechi, A.H., Albreem, M.A., Chaudhry, S.A., Zia, M.S., Kim, S., 2020. Sixth generation (6g)wireless networks: Vision, research activities, challenges and potential solutions.
[4]
Guo, W., 2020. Explainable artificial intelligence for 6g: Improving trust between human and machine. IEEE Communications Magazine 58, 39-45.
[5]
Hamilton, W.L., Ying, R., Leskovec, J., 2017. Inductive representation learning on large graphs. URL: https://arxiv.org/abs/1706.02216.
[6]
Ji, B., Wang, Y., Song, K., Li, C, Wen, H., Menon, V.G., Mumtaz, S., 2021. A survey of computational intelligence for 6g: Key technologies, applications and trends. IEEE Transactions on Industrial Informatics 17, 7145-7154. 2021.3052531.
[7]
Kipf, T.N., Welling, M., 2016. Semi-supervised classification with graph convolutional networks. URL: https://arxiv.org/abs/11609. 02907.
[8]
Latva-aho, M., Leppänen, K., 2019. 6g research visions: Key drivers and research challenges for 6g ubiquitous wireless intelligence. URL: https://www.6gflagship.com/key-drivers-and-research-challenges-for-6g-ubiquitous-wireless-intelligence/.
[9]
Letaief, K.B., Chen, W, Shi, Y, Zhang, I., Zhang, Y.I.A., 2019. The roadmap to 6g: Ai empowered wireless networks. IEEE Communications Magazine 57, 84-90.
[10]
Ma, L., Cheng, N., Wang, X., Sun, R., Lu, N., 2022. On-demand resource management for 6g wireless networks using knowledge-assisted dynamic neural networks, IEEE. pp. 1-6.
[11]
Maniak, T, Iqbal, R., Vujicic, Z., Karyotis, C, Passas, N., Doctor, R, 2022. Deep neural networks for transmission impairment mitigation in long-reach 5g access networks, IEEE. pp. 134-137. URL: https://ieeexplore.ieee.org/document/10002703/.
[12]
Nidhi, Mhovska, A., 2020. Small cell deployment challenges in ultradense networks: Architecture and resource management, IEEE. pp. 1-6.
[13]
Rodriguez, I., Koudouridis, G.P., Gelabert, X., Tayyab, M., Bassoli, R., Fitzek, F.H.P., Torre, R., Abd-Alhameed, R., Sajedin, M., Elfergani, I., Irum, S., Schulte, G., Diogo, P., Marzouk, R, Ree, M.D., Mantas, G., Politis, I., 2021. Secure virtual mobile small cells: A stepping stone toward 6g. IEEE Communications Standards Magazine 5, 28-36.
[14]
Sathya, V., Ghosh, S., Ramamurthy, A., Tamma, B.R., 2020. Small cell planning: Resource management and interference mitigation mechanisms in lte hetnets. Wireless Personal Communications 115, 335-361.
[15]
She, C, Dong, R., Gu, Z., Hou, Z., Li, Y, Hardjawana, W, Yang, C, Song, L., Vucetic, B., 2020. Deep learning for ultra-reliable and low-latency communications in 6g networks. IEEE Network 34, 219-225.
[16]
Shi, Y, Lian, L., Shi, Y, Wang, Z., Zhou, Y, Fu, L., Bai, L., Zhang, I., Zhang, W, 2023. Machine learning for large-scale optimization in 6g wireless networks. IEEE Communications Surveys and Tutorials 25, 2088-2132. 2023.3300664.
[17]
Sizer, T, Samardzija, D., Viswanathan, H., Le, S.T., Bidkar, S., Dom, P., Harstead, E., Pfeiffer, T, 2022. Integrated solutions for deployment of 6g mobile networks. lournal of Lightwave Technology 40, 346-357. JLT. 2021.3110436.
[18]
Tataria, H., Shafi, M., Molisch, A.R, Dohler, M., Sjoland, H., Tufvesson, R, 2021. 6g wireless systems: Vision, requirements, challenges, insights, and opportunities. Proceedings of the IEEE 109, 1166-1199. 2021.3061701.
[19]
University of Oulu, 2019. 1st 6g wireless summit. URL: http://www.6gsummit.com/2019/.
[20]
Velickovic, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y, 2017. Graph attention networks. URL: https://arxiv.org/abs/1710.10903.
[21]
Wang, X., Fu, L., Cheng, N., Sun, R., Luan, T, Quan, W, Aldubaikhy, K., 2022. loint flying relay location and routing optimization for 6g uav-iot networks: A graph neural network-based approach. Remote Sensing 14, 4377.
[22]
Yang, H., Alphones, A., Xiong, Z., Niyato, D., Zhao, I., Wu, K., 2020. Artificial-intelligence-enabled intelligent 6g networks. IEEE Network 34, 272-280.
[23]
Zhai, D., Wang, C, Cao, H., Garg, S., Hassan, M.M., AlQahtani, S.A., 2022. Deep neural network based uav deployment and dynamic power control for 6g-envisioned intelligent warehouse logistics system. Future Generation Computer Systems 137, 164-172. 2022.07.011.

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Procedia Computer Science
Procedia Computer Science  Volume 238, Issue C
2024
1088 pages
ISSN:1877-0509
EISSN:1877-0509
Issue’s Table of Contents

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2024

Author Tags

  1. graph neural networks
  2. 6G communications
  3. IoT communications
  4. small cells
  5. network deployment

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 23 Jan 2025

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media