Leveraging Machine Learning for Enhanced Green Radio over Fiber: Techniques, Challenges, and Future Prospects

The growing demand of energy-efficient communication systems has created an urge to explore the domains which may provide a possible solution to implement future wireless networks having reduced carbon footprints. Integration of two technologies i.e. RoF and Machine learning builds a communication system that provides the advantages of both the technologies and develops a system that can meet the standards required for future networks. Leveraging machine learning for enhanced communication aligns the come into being green radio systems with sustainable development goals making it worthy of implementing in real time future system. This paper presents a brief overview of machine learning techniques used in enhancing the performance of RoF systems and moves towards achieving more sustainable and reliable communication network. The paper also gives an insight to the merits and demerits of integrating RoF and machine learning and the challenges associated with implementing the models in real-time environment.