Subspace Aware Compressive Sensing Aided Detection for MIMO OFDM based ISAC

Abstract

In wireless communication systems, the temporal and spatial variations of the channel can significantly affect signal detection accuracy. Angular spread and Doppler effects further complicate the channel estimation process, highlighting the need for advanced signal processing techniques. In this study, we propose an Angular and Doppler Spread Aware Orthogonal Matching Pursuit (OMP) algorithm for Integrated Sensing and Communication (ISAC) systems. The proposed method estimates channel coefficients using basis decomposition in the angular domain while incorporating Doppler-induced phase shifts into the model. Designed to optimize both sensing and communication performance in ISAC systems, the proposed approach enhances the reliability of channel estimation, facilitating a more efficient interaction between communication and sensing tasks.