Deep Learning Modeling of a WBAN-MIMO Channel in Underground Mine

نویسندگان

چکیده

In this paper, an efficient model of the channel matrix is developed for 2 × Wireless Body Area Network Multiple Input Output (WBAN-MIMO) system, based on deep learning algorithms. The composed three Moreover, predicts simultaneously H in underground mine and identifies position collected data both Line Sight (LoS) Non-Line (NLoS) scenarios. trained evaluated using magnitude phase environment within frequency range 2.3 GHz – 2.5 GHz. These measurements, conducted with different antenna configurations LoS NLoS scenarios, constitute input to model. latest whether or NLoS. Finally, path loss impulse response models are compared measurements-based ones. modeled prediction exhibited lower Root Mean Square Error (RMSE) high classification accuracy LoS-NLoS identification, respectively. numerical results reveal that MIMO WBAN modeling offers a powerful solution future wireless systems environments.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2022

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2022.3185188