Quantum Approximate Optimization Algorithm for Wi-Fi CSI Processing and Reconstruction

This paper proposes a novel method to accentuate environmental features for Channel State Information (CSI) by leveraging the Quantum Approximate Optimization Algorithm (QAOA). The CSI Sub-channel Correlation (CSCC) used to represent environmental interactions between frequency-orthogonal subcarriers. The simulation results reveal that the CSCC distribution undergoes significant changes, while the mutual information with the original CSI increases when the Max-Cut problem is solved using QAOA. This enhancement in mutual information underscores the improved feature extraction capabilities of CSI, offering a promising direction for advanced Wi-Fi sensing applications.