Efficiency of Dynamic Radio Spectrum Management in Europe Through Artificial Intelligence

Abstract

With the increasing demand for wireless communications, effective spectrum management is becoming a key factor for the development of 5G and future 6G networks. Traditional static licensing methods show limitations in dynamic and heterogeneous network environments, which leads to the need for intelligent and adaptive solutions. The aim of this paper is to investigate the effectiveness of dynamic spectrum management using artificial intelligence (AI) in Europe, assessing the advantages and limitations of AI-based approaches compared to conventional methods and examining the role of European regulators in spectrum harmonisation and standardisation. The paper presents an analysis of key indicators such as spectral efficiency, spectrum utilisation, latency and energy efficiency, showing that AI-based models significantly increase efficiency, minimise interference and enable real-time adaptive traffic management. The main contribution of the study is to provide an integrated framework that links technological innovations, regulatory requirements and strategic recommendations for sustainable and intelligent spectrum management in the context of future 6G networks.