Robust Channel Assignment for Hybrid NOMA Systems with Condition Number Constrainted DRL

The Hybrid Non-Orthogonal Multiple Access (NOMA) is an alternative solution for future multiple access techniques, and the performance of hybrid NOMA systems relies on the quality of channel assignment. Conventional optimization approaches rely on the perfect Channel State Information (CSI), which hinders the deployment of the Hybrid systems. Deep Reinforcement Learning (DRL) approaches are robust...