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In this paper, we develop an intelligent channel im-pulse response (CIR) feature prediction algorithm in underwater networks. To this end, we first extract the major features, i.e., CIR values and tap distances, from raw CIR. Then, we implement a feature prediction module by adopting the time-series forecasting learning algorithm. Through the simulation results, we verify the prediction accuracy of the proposed algorithm with the normalized mean square error (NMSE) loss curve. © 2024 IEEE.
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