A Techno-Economic Analysis of New Market Models for 5G+ Spectrum Management

Abstract

While 5G has become a reality in several places around the world, some countries are still in the process of assigning frequency bands and deploying networks. In this context, there is a significant opportunity to explore new market models for the management and utilization of the radio spectrum. Access to the radio spectrum results in diverse competition schemes, where market behavior varies based on the regulator-defined access scheme and the competitive strategies of different actors. To thoroughly analyze potential competition scenarios, this work introduces a model that enhances the comprehension of market variables, emphasizing behaviors influenced by relationships. The model’s development leverages the potential of artificial intelligence and historical data from Colombia’s mobile telecommunications market. Intelligent spectrum sensing, based on Software Defined Radio, augments the model’s construction, utilizing lightweight AI algorithms to acquire real data on spectrum occupancy. In this way, the model provides novel insights into market dynamics, enabling the formulation of informed decision-making policies for regulatory bodies. Additionally, the application of causal machine learning (CausalML) helps understand the underlying causes of market behaviors, facilitating the design of guiding policies to maximize spectrum usage and foster competition. This approach demonstrates how AI-driven approaches and a deeper understanding of market dynamics can lead to effective 5G spectrum management, fostering a more competitive and efficient wireless communication landscape.

Keywords

• spectrum management
• causal machine learning
• telecommunications policy
• market models