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Reconfigurable intelligent surfaces (RISs) are one of the most promisingtechnological enablers of the next (6th) generation of wireless systems. Inthis paper, we introduce a novel use-case of the RIS technology in radiolocalization, which is enabling the user to estimate its own position viatransmitting orthogonal frequency-division multiplexing (OFDM) pilots andprocessing the signal reflected from the RIS. We demonstrate that userlocalization in this scenario is possible by deriving Cramer-Rao lower boundson the positioning error and devising a low-complexity position estimationalgorithm. We consider random and directional RIS phase profiles and apply aspecific temporal coding to them, such that the reflected signal from the RIScan be separated from the uncontrolled multipath. Finally, we assess theperformance of our position estimator for an example system and show that theproposed algorithm can attain the derived bound at high signal-to-noise ratiovalues.

RIS-Enabled Self-Localization: Leveraging Controllable Reflections With Zero Access Points