In collaboration with the Department of Economics, our research reimagines spectrum sharing as an AI-powered dynamic marketplace, optimizing spectrum allocation for next-generation wireless networks. Inspired by economic principles of supply, demand, and pricing, we develop game-theoretic and auction-based models where spectrum is traded, leased, or shared in real time. Leveraging reinforcement learning, blockchain for secure transactions, and predictive analytics, our framework ensures fair access, optimal pricing, and efficient utilization while preventing spectrum hoarding. This interdisciplinary approach integrates wireless communications, AI, and market economics, creating a self-regulating, decentralized ecosystem for 6G networks, IoT, and smart city applications.
