Enhanced channel estimation with atomic norm minimization and reconfigurable intelligent surfaces in mmWave MIMO systems

The performance of millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems has been significantly enhanced by the incorporation of dynamic reconfigurable intelligent surfaces (RIS). This paper proposes a novel dynamic channel estimation technique that combines dynamic atomic norm minimization with dynamic RIS to optimize RIS-aided mmWave MIMO systems. Leveraging the dynamic nature of both atomic norm minimization and RIS, the proposed approach efficiently adapts to changing environmental conditions, providing robust and accurate channel estimation. By dynamically optimizing the RIS configuration, the system achieves improved spectral and energy efficiency, enabling high-speed and reliable communication in challenging mmWave environments. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed dynamic channel estimation technique, highlighting its potential for enhancing the performance of future wireless communication systems. It presents a breakthrough dynamic channel estimation method for millimeter-wave (mmWave) multiple-input multiple-output systems that combines dynamic atomic norm minimization with reconfigurable intelligent surfaces (RIS). By adapting to environmental changes, this method significantly improves the accuracy of channel estimation. Dynamic RIS optimization increases spectral and energy efficiency and ensures fast and reliable communication in challenging mmWave environments. The simulations confirm the effectiveness of this system and show that it has the potential to revolutionize the future performance of wireless communications. image