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- W3010961559 abstract "Hybrid beamforming is a promising solution for multiple-input multiple-output (MIMO) systems with large scale antennas due to its low-cost and good performance compared with pure digital and analog beamforming. Unfortunately, conventional angle-of-arrival (AoA) estimation methods, such as MUSIC and ESPRIT algorithms, need a lot of calculations and must solve the issue of phase ambiguity. Therefore, this paper proposes a novel AoA estimation method based on layered ensemble learning. Because the training process can be completed off-line, only estimating complexity is taken into account which make the AoA detection process low complexity and meet real-time requirements. The simulation results indicate that the accuracy of the proposed AOA estimation method is higher than that of traditional algorithms. In addition, our proposed method is robust to the phase error." @default.
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- W3010961559 date "2019-10-01" @default.
- W3010961559 modified "2023-09-25" @default.
- W3010961559 title "A Novel Approach to Angle-of-Arrival Estimation Based on Layered Ensemble Learning" @default.
- W3010961559 doi "https://doi.org/10.1109/sips47522.2019.9020316" @default.
- W3010961559 hasPublicationYear "2019" @default.
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