<ul data-eligibleForWebStory="false"><li>This paper explores precoding design in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems using reconfigurable intelligent surfaces (RIS) to enhance transmissions.</li><li>Traditional exhaustive search for optimal codewords in the continuous phase shift is computationally intensive, prompting the use of permuted discrete Fourier transform (DFT) vectors and deep neural networks (DNN) to reduce complexity.</li><li>The DNN approach facilitates faster codeword selection, maintaining sub-optimal spectral efficiency in RIS-aided systems even with variations in the distance between end-users and the RIS.</li><li>Simulation results suggest the efficacy of DNN in enhancing the throughput of mmWave MIMO systems with obstructed direct communication paths.</li></ul>

DNN-Based Precoding in RIS-Aided mmWave MIMO Systems With Practical Phase Shift

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