Deep Learning-Based Detection Algorithm for the Multi-User MIMO-NOMA System
This work proposes a feedback-based deep neural network receiver for signal detection in MIMO-NOMA systems that integrates deep learning capabilities with iterative interference cancellation, enabling improved nonlinear signal separation and robustness against noise and inter-user interference.