Configuring Intelligent Reflecting Surface With Performance Guarantees: Blind Beamforming

This work gives a blind beamforming strategy for intelligent reflecting surface (IRS), aiming to boost the received signal-to-noise ratio (SNR) by coordinating phase shifts across reflective elements in absence of channel information. While existing methods IRS typically first estimate channels and then optimize shifts, we propose conditional sample mean based statistical approach that explores wireless environment via random sampling without performing any estimation. Remarkably, new method just requires polynomial number samples yield an SNR is quadratic elements, whereas standard random-max algorithm can only achieve linear under same condition. Moreover, gain additional insight into interpreting it as least squares problem. Field tests demonstrate significant advantages proposed over benchmark algorithms enhancing transmission.