  Conventional policy for configuring an intelligent reflecting surface (IRS)
typically requires channel state information (CSI), thus incurring substantial
overhead costs and facing incompatibility with the current network protocols.
This paper proposes a blind beamforming strategy in the absence of CSI, aiming
to boost the minimum signal-to-noise ratio (SNR) among all the receiver
positions, namely the coverage enhancement. Although some existing works
already consider the IRS-assisted coverage enhancement without CSI, they assume
certain position-channel models through which the channels can be recovered
from the geographic locations. In contrast, our approach solely relies on the
received signal power data, not assuming any position-channel model. We examine
the achievability and converse of the proposed blind beamforming method. If the
IRS has $N$ reflective elements and there are $U$ receiver positions, then our
method guarantees the minimum SNR of $\Omega(N^2/U)$ -- which is fairly close
to the upper bound $O(N+N^2\sqrt{\ln (NU)}/\sqrt[4]{U})$. Aside from the
simulation results, we justify the practical use of blind beamforming in a
field test at 2.6 GHz. According to the real-world experiment, the proposed
blind beamforming method boosts the minimum SNR across seven random positions
in a conference room by 18.22 dB, while the position-based method yields a
boost of 12.08 dB.
