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Enhanced Beam Alignment for Millimeter Wave MIMO Systems A Kolmogorov Model

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Document pages: 7 pages

Abstract: We present an enhancement to the problem of beam alignment in millimeter wave(mmWave) multiple-input multiple-output (MIMO) systems, based on a modificationof the machine learning-based criterion, called Kolmogorov model (KM),previously applied to the beam alignment problem. Unlike the previous KM, whosecomputational complexity is not scalable with the size of the problem, a newapproach, centered on discrete monotonic optimization (DMO), is proposed,leading to significantly reduced complexity. We also present aKolmogorov-Smirnov (KS) criterion for the advanced hypothesis testing, whichdoes not require any subjective threshold setting compared to the frequencyestimation (FE) method developed for the conventional KM. Simulation resultsthat demonstrate the efficacy of the proposed KM learning for mmWave beamalignment are presented.

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