TL;DR
The study concludes that AI provides an important foundation for developing more autonomous, efficient, reliable, secure, and adaptive NTN communication management systems.
A comprehensive survey of AI-enabled mobility management strategies for 5G, Beyond 5G, and upcoming 6G networks, with particular attention to HO optimization and load balancing is presented.
The findings revealed that AI enhances service reliability, reduces operational costs, minimizes latency, improves throughput, and supports proactive network management while ensuring compliance with Quality-of-Service requirements.
The evolution of advanced wireless communication has necessitated the transition from legacy networks toward more adaptable and intelligent sixth-generation (6G) architectures. Conventional radio access remains constrained in flexibility, intelligence, and scalability, limiting its ability to accommodate diverse and hi...
Energy management in battery-powered embedded Artificial Intelligence of Things (AIoT) nodes requires coordinated control of sensing, computation, and wireless communication. This structured review combines a documented search of Scopus, Web of Science Core Collection, and IEEE Xplore with screening of 548 unique recor...
An Adaptive Deep Reinforcement Learning (ADRL) based dynamic spectrum allocation framework for AVNs can ensure efficient spectrum allocation and reliable communication in a fast-growing network density and degraded channel environment and has stable convergence characteristics in its training behavior.
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