Fingerprint Matching Based 3-D Positioning for Cell-free Massive MIMO System

‍ ‍In this paper， we study the wireless positioning method based on fingerprint matching for cell-free massive multiple input multiple output （MIMO） system. It is assumed that a large number of access points （APs） are laid out in the service area， and each AP is configured with horizontal uniform linear array （ULA） or vertical ULA. The azimuth and elevation angles of users in different geographical locations were identified by orthogonal linear antenna arrays， and the azimuth and elevation angles fingerprint database were constructed by extracting the angle domain power spectrum matrix of wireless channel. The spectral clustering algorithm was used to preprocess the fingerprint database， then the fingerprint similarity was calculated by the two-stage fingerprint matching strategy. Based on the fingerprint similarity sorting， the reference point with the highest similarity with the user's fingerprint is searched in the fingerprint database. Finally， the weighted K-nearest neighbor （WKNN） algorithm is used to estimate the user's position. Simulation results show that the proposed scheme can obtain higher three-dimensional （3-D） positioning accuracy than single antenna scheme， ULA scheme and uniform rectangular array （URA） scheme.