Abstract

To address the moving-sensor localization problem in millimeter-wave (mm-wave) cell-free massive multiple-input multiple-output (MIMO) systems, a novel cooperative localization framework is proposed in this article. First, the angle of arrival (AoA) of the target sensor is extracted by each access point (AP) in the angle domain. Then, for the purpose of establishing the motion equation that is used to predict the location of the target sensor in the next period, a two-step velocity estimation algorithm is proposed to estimate the velocity and corresponding variance of the moving sensor simultaneously. Furthermore, based on horizontal dilution of precision (HDOP), an AP selection scheme is proposed to decide the subset of APs that participate in localization. On this basis, a time-sequential cooperative localization (TSCL) framework is constructed by jointly utilizing the estimated AoAs and the motion equation. The location estimation is converted to a joint posterior probability problem. The solution that maximizes the posterior probability is obtained through factor graph theory. The simulation results show that the proposed algorithm improves localization accuracy and robustness in time-varying environments.

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