  Reconfigurable intelligent surfaces (RISs) are one of the most promising
technological enablers of the next (6th) generation of wireless systems. In
this paper, we introduce a novel use-case of the RIS technology in radio
localization, which is enabling the user to estimate its own position via
transmitting orthogonal frequency-division multiplexing (OFDM) pilots and
processing the signal reflected from the RIS. We demonstrate that user
localization in this scenario is possible by deriving Cramer-Rao lower bounds
on the positioning error and devising a low-complexity position estimation
algorithm. We consider random and directional RIS phase profiles and apply a
specific temporal coding to them, such that the reflected signal from the RIS
can be separated from the uncontrolled multipath. Finally, we assess the
performance of our position estimator for an example system and show that the
proposed algorithm can attain the derived bound at high signal-to-noise ratio
values.
