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This paper discusses how to optimize the phase shifts of intelligentreflecting surface (IRS) to combat channel fading without any channel stateinformation (CSI), namely blind beamforming. Differing from most previous worksbased on a two-stage paradigm of first estimating channels and then optimizingphase shifts, our approach is completely data-driven, only requiring a datasetof the received signal power at the user terminal. Thus, our method does notincur extra overhead costs for channel estimation, and does not entailcollaboration from service provider, either. The main idea is to choose phaseshifts at random and use the corresponding conditional sample mean of thereceived signal power to extract the main features of the wireless environment.This blind beamforming approach guarantees an $N^2$ boost of signal-to-noiseratio (SNR), where $N$ is the number of reflective elements (REs) of IRS,regardless of whether the direct channel is line-of-sight (LoS) or not.Moreover, blind beamforming is extended to a double-IRS system with provableperformance. Finally, prototype tests show that the proposed blind beamformingmethod can be readily incorporated into the existing communication systems inthe real world; simulation tests further show that it works for a variety offading channel models.

Blind Beamforming for Intelligent Reflecting Surface in Fading Channels without CSI