Abstract
A channel prediction scheme with channel matrix doubling and temporal-spatial smoothing is proposed. With the assumption that the underlying channel model parameters are unchanged, a virtual doubled channel matrix is constructed to make full use of the intrinsic information contained in the CSI observations, then temporal-spatial smoothing technology is adopted to form the smoothed Hankel matrix, whose rows and columns are mutually space-correlated and time-correlated. After that, the multi-dimensional rotational invariance techniques algorithm is employed to estimate the channel model parameters, and finally time extrapolation is performed on the estimated channel model to predict the future channel state. By channel matrix doubling and temporal-spatial smoothing, the subspace estimation error can be significantly reduced and a more accurate channel model can be obtained, which leads to better channel prediction performance.
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Sun, D., Li, Y. A Channel Prediction Scheme with Channel Matrix Doubling and Temporal-Spatial Smoothing. Wireless Pers Commun 122, 2045–2055 (2022). https://doi.org/10.1007/s11277-021-08980-5
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DOI: https://doi.org/10.1007/s11277-021-08980-5