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- W4287071026 abstract "This paper introduces an identification method that determines whether a millimeter-wave wireless transmission using directional antennas is being established over a line-of-sight (LOS) or a non-line-of-sight (NLOS) cluster for indoor localization applications. The proposed technique utilizes the channel power angular spectrum that is readily available from a beam training process. In particular, the behavior of five different channel metrics, namely the spatial-domain, time-domain, and frequency-domain channel kurtosis, the mean excess delay, and the RMS delay spread, is analyzed using maximum likelihood ratio and artificial neural network. A noticeable difference between LOS and NLOS clusters is observed and assessed for identification. Hypothesis testing shows errors as low as 0.01-0.02 in simulation and 0.04-0.07 in measurements at 60 GHz." @default.
- W4287071026 created "2022-07-25" @default.
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- W4287071026 date "2021-07-20" @default.
- W4287071026 modified "2023-10-18" @default.
- W4287071026 title "Neural-Network-based NLOS Identification in Angular Domain at 60-GHz" @default.
- W4287071026 doi "https://doi.org/10.48550/arxiv.2107.09343" @default.
- W4287071026 hasPublicationYear "2021" @default.
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