Intelligent Detection for RIS-Assisted MIMO Systems: A First-and-Second Momentum Approach for 16-QAM
S. P. Azizi, H. -Y. Lu and S. -C. Cheng, "Intelligent Detection for RIS-Assisted MIMO Systems: A First-and-Second Momentum Approach," in IEEE Wireless Communications Letters, doi: 10.1109/LWC.2025.3542412. keywords: {Symbols;Massive MIMO;Complexity theory;Convergence;Vectors;Reflection;Deep learning;Channel estimation;Training;Reconfigurable intelligent surfaces;Reconfigurable intelligent surface;massive multiple-input multiple-output;deep learning},
Reconfigurable intelligent surface (RIS)-assisted massive multiple-input multiple-output (MIMO) is a potential technology for providing high-quality service in future communication systems. To further enhance system performance, in this letter, we propose a novel deep learning (DL) -based symbol detector, namely the DL-based first-and-second momentum detector (DFSM-Det). Specially, in each network layer, DFSM-Det utilizes the outputs from multiple previous layers to incorporate the mechanisms based on the double momentum to progressively refine symbol estimation layer by layer. Simulation results show that DFSM-Det achieves remarkably better performance than the existing DL-based detection schemes, particularly in highly loaded scenarios.