Sensing-assisted CSI feedback with echo prior information for mmWave massive MIMO systems

Abstract

Accurate acquisition of downlink channel state information (CSI) at the base station (BS) is crucial in frequency division duplex (FDD) millimeter wave (mmWave) massive multiple-input multiple-output (mMIMO) systems. Although compressive sensing (CS) and deep learning (DL)-based CSI feedback methods demonstrate their advantages, the recovery accuracy of downlink CSI still faces severe challenges due to the facts of high path loss, significant user equipment (UE) estimation errors, and typical compression requirements, etc. To tackle these issues, improving the accuracy of downlink CSI recovery has become an urgent task. Inspired by sensing-assisted communication techniques, an echo sensing information-assisted CSI feedback with echo sensing information method is proposed in this paper. In the proposed method, the communication echo signals observed at the BS are utilized to extract the dedicated sensing prior information for the downlink CSI recovery. With the extracted sensing prior information, a CSI denoising method is developed to suppress the non-path entries of the downlink CSI matrix in the angular-delay domain, thereby improving the recovery accuracy of downlink CSI at the BS. The proposed method establishes an embedding framework for improving the recovery accuracy of downlink CSI in FDD mmWave mMIMO systems. In this framework, the echo sensing information-assisted CSI recovery algorithm is directly embedded in the BS receiver to enhance the recovery accuracy of downlink CSI without modifying the UE transmitter. Simulation results demonstrate that the proposed method improves the recovery accuracy of downlink CSI compared to the classic DL-based and the CS-based CSI feedback methods. Furthermore, the proposed method exhibits its robustness against the impact of parameter variations.