Abstract
Reconfigurable intelligent surfaces (RISs) are a recent yet
revolutionary development in communications systems. Particularly
applicable to millileter wave (mmWave) systems, these surfaces can
increase localization performance and decrease vulnerability to
environmental influences, all by adjusting the incoming signals’ phase.
At the same time, manufacturing ideal hardware to be deployed at the
transceivers is not feasible nor practical. These non-linearities in
hardware, collectively known hardware impairments (HWIs), cause signal
degradation and adversely affect localization. In this paper, the effect
of HWIs on RIS-aided localization is examined. Towards that, the mean
squared error (MSE) of the user’s position is found through a maximum
likelihood estimator (MLE) and its functionality is verified by the
position error bounds (PEB), derived from Cramer-Rao lower bounds
(CRLB). Our numerical results show that active RISs mitigate the
deteriorating effect of HWIs on the user’s PEB. Based on our outcome,
increasing the inter-RISs space generally creates more resolvable paths
and leads to improved localization.