Spectrum and Power Allocation Using DRL in Cooperative Spectrum Sharing

This paper delves into optimizing joint spectrum and power allocation between a matched primary and secondary link pair in cooperative spectrum sharing. Weighted sum energy efficiency (WSEE) is adopted as the objective function to address the challenges of green communication. We propose a scheme based on deep reinforcement learning (DRL) to address this nonconvex spectrum and power allocation problem. Leveraging DRL, the spectrum and power allocation problem is autonomously optimized by only utilizing local information. Simulation results reveal that it achieves near-optimal performance and significantly enhances the network convergence speed with low computational overheads.