Utility-based Interference Coordination for Local Spectrum Licensing in 6G

This paper analyzes the consequences of increasing interference coordination between adjacent local networks for local licensing of spectrum in 6G. Building on the previously introduced pluralistic licensing concept, we propose adjusting interference levels to improve efficiency in terms of the total utility of the involved spectrum holders. To this end, we introduce a market-based perspective by incorporating utility to enhance coordination between adjacent networks. Through simulations, we show the potential efficiency gains in terms of utility for static and dynamic AI-based coordination mechanisms. In particular, the potential impact for interference coordination using a deep reinforcement learning algorithm, specifically the Proximal Policy Optimization (PPO), appears significant. Overall, interference coordination mitigates imperfections in a local spectrum market, leading to higher efficiency in terms of utility.