Abstract
In this paper, on phase noise of 5G NR mmWave systems, we propose a learning-based common phase error (CPE) estimation algorithm based on the denoising autoencoder serving as a nonlinear filter on the existing CPE estimators. The proposed algorithm learns the low dimension manifold of phase noise distributions with high probability. Traditional CPE methods have limitation when the time domain pilots are few, which causes degraded system performance with CPE interpolation. Besides accurate CPE estimation, the proposed method is more robust to various FR2 channels, Doppler effects, and the numerologies. Simulation results show that block error rate (BLER) could be improved up to 1.43 dB on SNR.
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