  In this paper we study the use of the Channel State Information (CSI) as
fingerprint inputs of a Convolutional Neural Network (CNN) for localization. We
examine whether the CSI can be used as a distinct fingerprint corresponding to
a single position by considering the inconsistencies with its raw phase that
cause the CSI to be unreliable. We propose two methods to produce reliable
fingerprints including the phase information. Furthermore, we examine the
structure of the CNN and more specifically the impact of pooling on the
positioning performance, and show that pooling over the subcarriers can be more
beneficial than over the antennas.
