Cooperative Fingerprint Positioning for Cell-Free Massive MIMO Systems

Cell-free massive multiple-input multiple-output (MIMO) is an emerging technology for next-generation wireless communication. In this paper, we propose a new cooperative fingerprint positioning method for cell-free massive MIMO systems. By performing discrete Fourier transform (DFT) on the channel matrix, we obtain the angle-domain channel power matrix and extract it as fingerprint information. Then according to the relationship of angles between users and different access points (APs), the angle similarity coefficient is proposed to judge the similarity between fingerprints. Through the application of the spectral clustering algorithm, we cluster the extracted fingerprint information of reference points, which improves the efficiency of fingerprint matching. Finally, using fingerprint matching and the weighted K-nearest neighbor (WKNN) algorithm, we get the estimated location of the user. The results show that the cooperative fingerprint positioning technology based on the angle similarity has good positioning performance.