Sensing Information-Assisted CSI Feedback

Due to the limited transmission resources, as well as the limited computing resources and battery energy of user equipment (UE), the estimated downlink channel state information (CSI) is typically off-grid, deteriorating the channel sparsity and recovery accuracy of the downlink CSI at the base station (BS). To address these issues, we propose a sensing information-assisted CSI feedback method to recover the off-grid downlink CSI at the BS. Specifically, the proposed method utilizes the sensing information from distinct data modality to form the off-grid prior information. Subsequently, by leveraging the off-grid prior information and the received CSI, the complex path gain of the downlink CSI is recovered. Finally, a high resolution grid is constructed to recover the off-grid CSI matrix, thereby enhancing the recovery accuracy. Simulation results demonstrate that the proposed method effectively mitigates the off-grid effect of the downlink CSI at the BS. Furthermore, the proposed method presents performance improvement and robustness against parameter variations when compared to other methods.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-12-11
DOI
https://doi.org/10.1109/lcomm.2024.3515973
Citations
5
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
1.74

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article

Sensing Information-Assisted CSI Feedback

Chaojin Qing, Zilong Wang, Linsi He, Yu Sun et al.
5 citations
IEEE Communications Letters
Neural Networks and Applications
1.74
article

Sensing Information-Assisted CSI Feedback

Chaojin Qing, Zilong Wang, Linsi He, Yu Sun, Yuqiao Yang, Haowen Jiang
article en
5 citations

Abstract

Due to the limited transmission resources, as well as the limited computing resources and battery energy of user equipment (UE), the estimated downlink channel state information (CSI) is typically off-grid, deteriorating the channel sparsity and recovery accuracy of the downlink CSI at the base station (BS). To address these issues, we propose a sensing information-assisted CSI feedback method to recover the off-grid downlink CSI at the BS. Specifically, the proposed method utilizes the sensing information from distinct data modality to form the off-grid prior information. Subsequently, by leveraging the off-grid prior information and the received CSI, the complex path gain of the downlink CSI is recovered. Finally, a high resolution grid is constructed to recover the off-grid CSI matrix, thereby enhancing the recovery accuracy. Simulation results demonstrate that the proposed method effectively mitigates the off-grid effect of the downlink CSI at the BS. Furthermore, the proposed method presents performance improvement and robustness against parameter variations when compared to other methods.

IEEE Communications LettersVol. 29(2)
Xihua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Neural Networks and Applications
1.74
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