Deep Joint CSI Feedback and Multiuser Precoding for MIMO OFDM Systems
<|reference_start|>Deep Joint CSI Feedback and Multiuser Precoding for MIMO OFDM Systems: The design of precoding plays a crucial role in achieving a high downlink sum-rate in multiuser multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. In this correspondence, we propose a deep learning based joint CSI feedback and multiuser precoding method in frequency division duplex systems, aiming at maximizing the downlink sum-rate performance in an end-to-end manner. Specifically, the eigenvectors of the CSI matrix are compressed using deep joint source-channel coding techniques. This compression method enhances the resilience of the feedback CSI information against degradation in the feedback channel. A joint multiuser precoding module and a power allocation module are designed to adjust the precoding direction and the precoding power for users based on the feedback CSI information. Experimental results demonstrate that the downlink sum-rate can be significantly improved by using the proposed method, especially in scenarios with low signal-to-noise ratio and low feedback overhead.<|reference_end|>
@article{guo2024deep,
    title={Deep Joint CSI Feedback and Multiuser Precoding for MIMO OFDM Systems},
    author={Yiran Guo, Wei Chen, Jialong Xu, Lun Li, Bo Ai},
    journal={arXiv preprint arXiv:2404.16289},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.16289},
    primaryClass={cs.IT eess.SP math.IT}
}