Estimation of Uplink Channels for Multiple Users Using Tensor Modeling in RIS-Aided MISO Communication

Abstract

In this paper estimation of uplink channels using tensor modeling is addressed for multiple users in a reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) communication. The coherence interval is divided into structured frames of pilot symbols transmitted by the users and pattern of phase shifts applied by the RIS in order to estimate the base station (BS)-RIS channels and the RIS-user’s channels. Estimation methods that use tensor modeling including Khatri-Rao Factorization (KRF) and bilinear alternating least squares (BALS) are applied to the signal model. Numerical results show that both KRF and BALS are superior to the LS estimator by 10 dB SNR for the correlated Rayleigh fading channel model.

Keywords

• reconfigurable intelligent surfaces
• multi-user miso
• channel estimation
• least squares
• khatri-rao factorization
• parallel factor decomposition