Abstract
A reconfigurable intelligent surface (RIS) can shape the radio propagation environment by virtue of changing the impinging electromagnetic waves towards any desired directions, thus, breaking the general Snell's reflection law. However, the optimal control of the RIS requires perfect channel state information (CSI) of the individual channels that link the base station (BS) and the mobile station (MS) to each other via the RIS. Thereby super-resolution channel (parameter) estimation needs to be efficiently conducted at the BS or MS with CSI feedback to the RIS controller. In this paper, we adopt a two-stage channel estimation scheme for RIS-aided millimeter wave (mmWave) MIMO systems without a direct BS-MS channel, using atomic norm minimization to sequentially estimate the channel parameters, i.e., angular parameters, angle differences, and the products of propagation path gains. We evaluate the mean square error of the parameter estimates, the RIS gains, the average effective spectrum efficiency bound, and average squared distance between the designed beamforming and combining vectors and the optimal ones. The results demonstrate that the proposed scheme achieves super-resolution estimation compared to the existing benchmark schemes, thus offering promising performance in the subsequent data transmission phase.
Highlights
T HE millimeter wave bands with multiple-input multiple-output (MIMO) transmission is a promising candidate for 5G and beyond 5G communication systems [1]
We have studied the channel estimation (CE) problem for the reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) MIMO systems and proposed a two-stage atomic norm minimization problem, which can efficiently perform super-resolution channel parameter estimation
The power maximization criterion has been utilized to guide the design of phase control matrix at the RIS, followed by joint design of beamforming and combining vectors at the base station (BS) and mobile station (MS) based on the reconstructed composite channel
Summary
T HE millimeter wave (mmWave) bands with multiple-input multiple-output (MIMO) transmission is a promising candidate for 5G and beyond 5G communication systems [1]. In our recent work [34], we applied the iterative reweighted method of [7], [38] to estimate the channel parameters Both BS-RIS and RIS-MS channels were assumed to have only a LoS path. Unlike all the aforementioned literature, a multilevel hierarchical codebook based scheme was leveraged to design the phase control matrix (reflection beam) at the RIS and the combining vector at the MS jointly [39] instead of estimating the MIMO channel parameters as an intermediate step towards joint design of active combining vector at the MS and passive beamforming (BF) at the RIS.
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