Artificial Intelligence-Based Energy Efficiency Models in Green Communications Towards 6G

Abstract

The information sector has always aspired to use green communications to minimize energy consumption and use fewer fossil fuels. There seems to be a certain amount of network framework and several associated terminals will advance to enlarge exponentially in the modern 5G and forthcoming 6G regimes, resulting in increased energy costs. The focused advancement of green communications is becoming more and more crucial and essential. However, it is undeniable that the commitment to quality of service, encryption, adaptability, and cognition in 6G will become more demanding and diversified, which will provide challenges for energy-efficient advancement. The mechanism for compelling energy harvesting, which will be extensively used all along 6G, nevertheless makes the network maintenance and power regulation more complicated. To conquer these challenges and diminish human efforts. Artificial intelligence (AI) approaches are the most recognized for present-day applications. Research has been conducted comprehensively in academia and industry to mitigate energy claims, and advance energy efficiency to regulate energy accumulation in different networking schemes. The critical factors for green communications are well addressed in this study, together with the associated research review on AI-positioned green communications. Emphasis is given to various methods and approaches employed in the green era to establish plans and enable greater efficiency. To curtail algorithm complications with high accuracy in forthcoming 6G, the analysis of machine learning techniques, including cutting-edge technologies like deep learning, conventional AI techniques, and analytical models were proposed future directions of research in AI models towards a green 6G. © 2024 selection and editorial matter, Dr. Abraham George and G. Ramana Murthy; individual chapters, the contributors.