Adaptive 6G Wireless Communication System Using Machine Learning for Optimized Data Transmission

Overall, the simulation demonstrates efficient network performance with high bandwidth, low latency, and minimal packet loss, indicating reliable and stable communication. The path details further show optimized routing with a shorter path length and fewer hops, which helps in reducing delay and improving data transmission speed. The use of shortest path algorithms ensures that data travels through the most efficient route, enhancing overall network performance. These results highlight the importance of intelligent routing, clustering, and performance monitoring in advanced communication systems like 6G networks, enabling better resource utilization, faster communication, and improved system reliability

[1] M. Usama, J. Qadir, and A. Al-Fuqaha, “Machine learning for network automation: Overview, architecture, and applications,” IEEE Communications Surveys & Tutorials, vol. 26, no. 2, pp. 890–943, 2024.  [2] S. Kumar and K. Dutta, “Clustering algorithms for wireless networks: A comprehensive survey,” IEEE Access, vol. 11, pp. 45678–45702, 2023.  [3]A. Khraisat, I. Gondal, P. Vamplew, and J. Kamruzzaman, “Machine learning-based intrusion detection systems: A systematic literature review,” IEEE Access, vol. 11, pp. 78234–78267, 2023. [4] Y. Liu, X. Wang, and Z. Qin, “Artificial intelligence enabled intelligent communication networks: Architecture and future directions,” IEEE Network, vol. 37, no. 2, pp. 102–109, 2023. [5] M. Chen, Y. Miao, X. Jian, X. Wang, and I. Humar, “Cognitive machine learning for intelligent wireless networks: A survey,” IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp. 92–118, 2022. [6] R. Vinayakumar, M. Alazab, K. P. Soman, P. Poornachandran, A. Al-Nemrat, and S. Venkatraman, “Network attack detection using machine learning: Techniques, datasets and challenges,” IEEE Transactions on Network and Service Management, vol. 19, no. 4, pp. 4876–4898, 2022. [7] H. Zhang, W. Liu, Q. Chen, and Z. Han, “Quality of service in next-generation networks: Challenges and solutions,” IEEE Communications Magazine, vol. 60, no. 8, pp. 42–48, 2022. [8] S. Althunibat, M. Alenezi, and A. Albugami, “Energy-efficient node management in wireless sensor networks using machine learning techniques,” IEEE Access, vol. 10, pp. 65843–65858, 2022. [9] J. Tang, F. Liu, and Y. Zhou, “Secure routing and anomaly detection in next-generation communication networks using artificial intelligence,” IEEE Transactions on Network and Service Management, vol. 19, no. 3, pp. 2751–2764, 2022. [10] L. Zhang, H. Ji, and X. Li, “Adaptive resource allocation and intelligent optimization for future wireless communication systems,” IEEE Internet of Things Journal, vol. 9, no. 14, pp. 11890–11903, 2022.