AI Driven Network Optimization for 6G Wireless Systems

Authors

  • Rahul Vadisetty Electrical Engineering wayne state university Detroit, MI, USA rahulvy91@gmail.com Author

Keywords:

Quantum Cloud Computing (QCC), Artificial Intelligence (AI), 6G Wireless Systems, Global Education Networks, Personalized Learning, Connectivity.

Abstract

The evolution of global education networks demands innovative technological solutions to address the growing needs for enhanced connectivity, accessibility, and personalized learning experiences. This paper explores the potential of integrating Quantum Cloud Computing (QCC) with Artificial Intelligence (AI) and 6G wireless systems to revolutionize next-generation learning environments. By leveraging the computational power of quantum cloud technologies and the ultra-fast, lowlatency capabilities of 6G networks, this study proposes a novel framework for optimizing global education networks. The integration of AI facilitates personalized learning experiences through advanced data analytics, real-time feedback, and adaptive learning paths. This paper presents a comprehensive analysis of how QCC and 6G can address current challenges in education, including connectivity issues, scalability, and resource management. Key performance metrics such as latency, bandwidth, throughput, and data reliability are examined to demonstrate the potential improvements in educational delivery and access. The findings suggest that this integration not only enhances the efficiency and effectiveness of global education networks but also supports equitable access to high-quality education across diverse regions. This study highlights the transformative impact of combining QCC, AI, and 6G technologies on the future of education and provides a framework for future research and development in this field.

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Published

2018-05-02

How to Cite

AI Driven Network Optimization for 6G Wireless Systems. (2018). International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 9(1), 57-89. https://ijmlrcai.com/index.php/Journal/article/view/100

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