An integrated analysis of AI networks and wireless communication (E-mail)
The integration of artificial intelligence (AI) into wireless communication networks represents a transformative shift in the telecommunications landscape. This analysis explores the synergistic relationship between AI networks and wireless communication, particularly in the context of emerging technologies like 5G and 6G. AI enhances various aspects of wireless networks, including network management, spectrum optimization, and security. By leveraging machine learning algorithms, operators can analyse vast amounts of data to predict network demand, optimize resource allocation, and automate maintenance processes. This capability is crucial as the number of connected devices is expected to exceed 30 billion by 2025, necessitating efficient management of network resources. The architecture of future wireless networks will likely incorporate multiple AI layers—intelligent sensing, data analytics, intelligent control, and smart applications—to facilitate real-time decision-making and resource management. These advancements not only improve operational efficiency but also enhance user experience by minimizing latency and increasing reliability. Moreover, AI's role in cybersecurity within wireless networks is becoming increasingly vital, as it can detect anomalies and respond to potential threats more swiftly than traditional methods. The convergence of AI and wireless communication is set to redefine how networks operate, ensuring they can meet the demands of an increasingly connected world while maintaining high performance and security standards. This integrated analysis underscores the importance of ongoing research and development in AI-enabled wireless technologies to harness their full potential for future applications. Furthermore, the collaboration between AI and wireless communication fosters innovations in Internet of Things (IoT) applications, smart cities, and autonomous.
Authors
- Rahul G Ingle (ORCID: https://orcid.org/0000-0001-5987-0041)
- Vaibhav C. Kapile
Institutions
- Datta Meghe Institute of Higher Education and Research (IN)
Publication Details
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1109/idicaiei61867.2024.10842742
- Citations
- 1
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.33