Hybrid RIS-Enabled Individual Channel Estimation for MIMO Systems Using Efficient Decoupled Atomic Norm Minimization

In multiple-input multiple-output (MIMO) communication systems, the reconfigurable intelligent surfaces (RIS) has been recognized as one of the key technologies to enhance system performance. This paper introduces a hybrid RIS architecture integrated with dynamically controllable active elements, which reduces the cost of RIS deployment. Based on this architecture and the sparsity characteristic of millimeter-wave channels, we propose an atomic norm minimization (ANM)-based method for individual channel estimation. This method maximizes the decoupling of high-dimensional coupled parameters, further reducing the computational complexity of estimating for individual channels while ensuring estimation performance. Simulation experiments demonstrate that the proposed method not only achieves higher estimation performance but also exhibits a significant advantage in computational time compared to orthogonal matching pursuit.