| 引用本文: | 赵彬,徐骏,张云,朱翔.新一代Wi-Fi的新型感知信息压缩方法[J].哈尔滨工业大学学报,2024,56(5):12.DOI:10.11918/202201090 |
| ZHAO Bin,XU Jun,ZHANG Yun,ZHU Xiang.A new perceptual information compression method based on next generation Wi-Fi standard[J].Journal of Harbin Institute of Technology,2024,56(5):12.DOI:10.11918/202201090 |
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| 摘要: |
| 通信设备由于和雷达设备的工作存在重叠,也可以实现目标检测。但是传统的通信协议采用显式反馈传输信息,导致采用通信设备检测无法保留感知信息,因此可以对显式反馈的分解流程进行改进,从而在通信的间隙实现对环境目标的感知。在MIMO系统中,波束成型是发射端利用MIMO信道状态信息生成导向矩阵,从而提升接收端接收性能的一种技术。目前显式反馈波束成型是通信中波束成型的主流方式,接收端会对接收到的信道矩阵进行奇异值分解后转换成一系列角度值传回发射端。虽然采用传统的矩阵分解流程获得反馈矩阵可以有效降低反馈的冗余信息量,但是通常会丢失掉通信设备在感知过程中获得的大部分重要信息,从而导致利用Wi-Fi信号进行目标探测的功能受到限制。研究发现对于接收到的信道矩阵利用传统的分解方式获得的反馈矩阵特征向量无法保留目标的距离,速度信息。本文提出了一种新型的分解方式,基于信道矩阵的协方差矩阵,先求解左奇异矩阵,再利用左右两个酉矩阵正交向量的对应关系,进一步求解从而获得改进的右奇异矩阵,所提改进方法保留了目标的距离、速度以及角度信息,极大地提升了有效反馈信息量。最后通过仿真实验验证了所提方法的有效性。 |
| 关键词: MIMO 波束成型 显式反馈 奇异值分解 |
| DOI：10.11918/202201090 |
| 分类号:TN929.5 |
| 文献标识码:A |
| 基金项目:国家自然基金面上项目(62371170) |
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| A new perceptual information compression method based on next generation Wi-Fi standard |
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ZHAO Bin,XU Jun,ZHANG Yun,ZHU Xiang
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(School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China)
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| Abstract: |
| Due to the overlapping functionality between communication devices and radar systems, communication devices can also be utilized for target detection. However, traditional communication protocol adopts explicit feedback to transmit information, leading to the failure of communication equipment detection to retain perceptual information. Therefore, the decomposition process of explicit feedback can be improved, so as to realize the awareness of environmental objectives in the communication gap. In MIMO systems, beamforming is a technology used at the transmitter to generate a steering matrix based on MIMO channel information, thereby enhancing the channel performance at the receiver. At present, display feedback beamforming is the mainstream approach of beamforming in communication. However, the feedback matrix obtained by the traditional decomposition method usually loses some important information, which limits the functionality of using Wi-Fi signals for target detection. It is found that the eigenvector obtained by the traditional singular value decomposition method can not retain the distance and velocity information of the target. In this paper, a novel decomposition method is proposed based on the covariance matrix of the channel matrix. Firstly, the left singular value matrix is obtained, and then an improved right singular value matrix is further obtained by using the corresponding relationship between the orthogonal vectors of the two unitary matrixes. The improved result retains the distance, speed and angle information of the target, and greatly improves the effectiveness of the feedback information. Finally, the effectiveness of the proposed method is verified through simulation. |
| Key words: MIMO beam forming explicit feedback singular value decomposition |
