Low-Complexity Channel Parameter Estimation for Coprime HRIS-Assisted MIMO Systems

This paper proposes a parameter estimation scheme for uplink MIMO systems assisted by a Hybrid Reconfigurable Intelligent Surface (HRIS). To reduce hardware complexity, the HRIS employs a small number of active elements arranged in a sparse coprime geometry for local sensing, while the remaining elements passively reflect signals. This simultaneous sensing and reflection significantly improves accuracy over fully passive architectures. The method leverages Khatri-Rao and Kronecker factorizations to efficiently decouple the cascaded channel at the base station. Furthermore, spatial smoothing resolves the coprime array rank deficiency, enabling robust angular extraction via Root-MUSIC. Simulations demonstrate highly resilient estimation performance across scenarios.