Channel Estimation for RIS-Aided mmWave MIMO Systems via Atomic Norm Minimization

A reconfigurable intelligent surface (RIS) can shape the radio propagation environment by virtue of changing impinging electromagnetic waves towards any desired directions, thus, breaking general Snell's reflection law. However, optimal control RIS requires perfect channel state information (CSI) individual channels that link base station (BS) and mobile (MS) to each other via RIS. Thereby super-resolution (parameter) estimation needs be efficiently conducted at BS or MS with CSI feedback controller. In this paper, we adopt a two-stage scheme for RIS-aided millimeter wave (mmWave) MIMO systems without direct BS-MS channel, using atomic norm minimization sequentially estimate parameters, i.e., angular angle differences, products path gains. We evaluate mean square error parameter estimates, gains, average effective spectrum efficiency bound, squared distance between designed beamforming combining vectors ones. The results demonstrate proposed achieves compared existing benchmark schemes, thus offering promising performance in subsequent data transmission phase.