Configuring Intelligent Reflecting Surface With Performance Guarantees: Blind Beamforming

This paper proposes a blind beamforming strategy for intelligent reflecting surface (IRS), aiming to boost the signal-to-noise ratio (SNR) by coordinating phase shifts across the reflective elements in the absence of channel information. Differing from most existing approaches that first estimate channels and then optimize phase shifts, the proposed blind beamforming method explores the wireless environment by extracting statistical features directly from random samples of the received signal power, without acquiring channel station information (CSI). This new method just requires a polynomial number of random samples to provide a quadratic SNR boost in the number of reflective elements without CSI, whereas the standard random-max sampling algorithm can only achieve a linear boost under the same condition. Moreover, we interpret blind beamforming from a least-squares point of view. Field tests demonstrate the significant advantages of the proposed blind beamforming approach over the benchmark methods in enhancing wireless transmission.