Beyond 5G: Exploring AI-Driven Network Optimisation for 6G Communications - Meher, Kunal; Karthikeyan, S.; Ranjan Sahu, Bharat Jyoti; Sunil, M.P.; Mishra, Smita; Singh, Amanveer; Tejesh, Kukatla (International Journal of Engineering, Science and Information Technology, 2025)
This research consists of various features of 5G networks; the vision for 6G networks promises significant advancements, including ultra-high data rates, sub-millisecond latency, highly intelligent network operations, and exceptional device interconnectivity, among others.  Artificial Intelligence (AI) meets these requirements, which act as a fundamental base in self-organising and proactive adaptive network management. In the scope of this paper, AI integration with core 6G network functions is considered, including AI techniques such as machine learning, deep learning, federated learning, and reinforcement learning. Focus is on the AI-driven optimisation of spectrum utilisation, user experience, traffic pattern prediction, dynamic network slicing, robust QoS, and responsive QoS retention. Advancing edge computing, reconfigurable intelligent surfaces (RIS), and digital twins are also discussed. The study also discusses the lack of AI governance in 6G infrastructure, which includes data privacy, transparency of the algorithms, energy expenses, and global standardisation. This research focus reveals the highlights of the primary gaps in design and governance rationale that emerge through the lack of AI-integrated structural frameworks, resigns through the absence of a designed fabric needed to supplant the transcending potential of 6G enabled autonomous communication systems AI will irrevocably purge and define the naivety behind detonating the boundless potential AI entrenched paradigms will deliver.