基于 beamforming 反馈矩阵的 Wi-Fi 感知 研究

通信感知一体化（Integrated Sensing and Communication）被认为是下一代通信 系统的重要特征之一。作为一个非常有前景的技术方向，近年来，通信感知一体 化的相关技术已经引起了学术界和工业界越来越多的关注。在学术研究中，已经 被证明了有许多可行的应用可以通过商品 Wi-Fi 设备实现，例如：Wi-Fi 感知。在 工业界，一个名为 WLAN Sensing（也称为 IEEE 802.11bf）的任务组由 IEEE 标准 协会成立于 2020 年，以提供用 Wi-Fi 信号进行感知的标准支持。 Wi-Fi 感知是指，通过 Wi-Fi 信号观测到与环境相关的信道状态信息（Channel State Information，CSI），然后这些 CSI 可以被广泛用于不同目的的感知。据我们 所知，到目前为止，Wi-Fi 感知的大部分研究都是基于完整的信道状态信息进行的。 然而，从 IEEE 802.11ac 开始，压缩的信道状态信息是今后 Wi-Fi 标准中唯一被支 持的反馈类型。这就意味着，这些 Wi-Fi 感知的相关研究只能在可以获取到完整 CSI 的接收侧进行。因此，本文旨在对基于压缩的信道状态信息的 Wi-Fi 感知进行 全面的研究，以使得在发射侧的感知成为可能。 在 MIMO（Multiple-Input Multiple-Output）系统中，发送端波束成形（Beam forming）是一种常见的用于改善通信质量的信号处理技术。在信道监听阶段，接 收端需要对发送端发送的监听帧进行信道估计。在有限反馈情况下，还需要对估 计出的信道矩阵进行矩阵分解得到 beamforming 反馈矩阵，并且压缩反馈给发送 端。最终，发送端通过 beamforming 反馈矩阵对发送信号进行预编码，从而实现波 束成形。由于 beamforming 反馈矩阵一般是通过对 CSI 进行矩阵分解得到的压缩 信道状态信息，显然，不同的分解方式对于感知性能来说会产生不同的影响。本 文主要是对单用户场景下基于压缩信道状态信息的 Wi-Fi 感知进行了研究。一方 面是对矩阵分解方式及相应的反馈方案的研究，具体研究了奇异值分解（Singular Value Decomposition，SVD）和正交三角分解（QR Decomposition，QRD）两种分 解方式，并对各自不同的反馈方案及感知性能进行了分析。另一方面，也对上述 反馈方案的通信性能进行了考量。本文通过仿真以及进一步的实验，从感知和通 信的角度分别对不同反馈方案进行了性能分析和比较，并最终提出了一个感知和 通信功能融合的系统，以实现感知和通信功能一体化。

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