Revolutionizing Spectrum Management: Data-Driven Strategies

Authors:
Publisher website
Google Scholar
Abstract
Effective spectrum management is essential with the growing demand for wireless services and the increasing complexity of spectrum usage scenarios. However, regulatory authorities often encounter limitations in resource availability, posing challenges to their ability to efficiently manage the finite radio frequency spectrum. In response to these challenges, data-driven methodologies and the judicious use of artificial intelligence (AI) have emerged as promising approaches to enhance spectrum management practices. In this article, it is reasoned that the adoption of AI and data-driven approaches in spectrum management not only mitigates resource constraints but also enables regulators to automate routine tasks, streamline processes, and allocate their limited resources more effectively, allowing personnel to focus on higher-value activities.

This publication has 9 references indexed in Scilit: