Evolution Toward Data-Driven Spectrum Sharing: Opportunities and Challenges

Abstract

As the demand for wireless services continues to grow, the need for efficient and effective management of the radio frequency (RF) spectrum becomes increasingly important. A spectrum management approach based on data analysis and interpretation i.e. data-driven, offers a solution as it provides valuable insights into spectrum usage patterns, demand, and the potential for harmful interference in shared spectrum scenarios. This paper focuses on the opportunities and challenges of incorporating diverse data sources into the management of spectrum, with a specific emphasis on spectrum sharing, particularly within database-assisted spectrum sharing systems. The benefits of adopting a data-driven approach to these systems are demonstrated through simulation of specific case studies. These studies indicate the potential for achieving up to a 60% greater density of spectrum use compared to conventional approaches, while also effectively managing harmful interference.

Keywords

• Data-driven spectrum management
• database-assisted spectrum sharing
• dynamic spectrum access