  This paper develops fundamental bounds for localization in orthogonal
frequency division multiplexing (OFDM) systems aided by reconfigurable
intelligent surfaces (RISs). Specifically, we start from the assumption that
the position and orientation of a RIS can be viewed as prior information for
RIS-aided localization in wireless systems and derive Bayesian bounds for the
localization of a user equipment (UE). To do this, we first derive the Bayesian
Fisher information matrix (FIM) for channel parameters to derive the Bayesian
localization bounds. Then, to focus on the geometric channel parameters, we
derive the equivalent Fisher information matrix (EFIM) and show that it has a
definite structure. Subsequently, we show through the information loss
associated with the EFIM that when the RIS reflection coefficients remain
constant across all OFDM symbols, and there is no prior information about the
nuisance parameters, the corresponding submatrix in the EFIM related to the RIS
angle parameters is a zero matrix. As a result of the EFIM being a zero matrix,
estimating the RIS-related angle channel parameters is not possible when the
RIS reflection coefficients remain constant across all OFDM symbols. This
observation is crucial for the estimation of the RIS-related angle parameters.
It dictates that to estimate the RIS-related angle parameters, there must be
more than one OFDM transmission with differing RIS reflection coefficients.
