基于有效载荷的OFDM-ISAC中与星座无关的距离估计
Constellation-Independent Range Estimation in Payload-Based OFDM-ISAC
AI总结：
本文提出了一种区域感兴趣区域不匹配滤波器（ROI-MMF），用于抑制多目标和杂波环境中由非恒模数调制符号引起的数据依赖性旁瓣，同时保持主瓣响应，从而提高距离估计性能。
AI中文摘要：
正交频分复用（OFDM）是由于其频谱效率和与现代无线标准的兼容性而成为集成感知与通信（ISAC）的关键波形。然而，在多目标和杂波丰富的环境中，基于有效载荷的OFDM-ISAC可能会受到非恒模数调制符号引起的数据依赖性旁瓣的影响。为克服这些限制，本文提出了一种区域感兴趣区域不匹配滤波器（ROI-MMF），该滤波器在指定的延迟区域内抑制旁瓣，同时保持主瓣响应。通过利用Woodbury恒等式，所提出的设计允许高效闭合形式的实现，其复杂度与ROI大小成正比，而不是子载波数量。我们理论上提供了所设计ROI-MMF的测距均方误差（MSE），证明其性能优于传统匹配滤波（MF）和互易滤波（RF）感知接收机。在各种星座下的仿真显示，所提出的感知接收机的测距MSE接近Cramér-Rao界（CRB），这证实了即使在非恒模数星座下，我们的设计也能保持目标测距性能。最后，该框架通过我们的空中OFDM-ISAC测试台进行了实验验证。
英文摘要：
Orthogonal frequency division multiplexing (OFDM) is a key waveform for integrated sensing and communication (ISAC) due to its spectral efficiency and compatibility with modern wireless standards. In multi-target and clutter-rich environments, however, payload-based OFDM-ISAC can suffer from data-dependent sidelobes induced by non-constant-modulus modulation symbols. To overcome these limitations, this paper proposes a region-of-interest mismatched filter (ROI-MMF) that suppresses sidelobes within a prescribed delay region while preserving the mainlobe response. By leveraging the Woodbury identity, the proposed design admits an efficient closed-form implementation whose complexity scales with the ROI size rather than the number of subcarriers. We theoretically provide the ranging mean-square error (MSE) of the designed ROI-MMF, which shows the superior performance compared to conventional matched filtering (MF) and reciprocal filtering (RF) sensing receivers. Simulations across various constellations show that the proposed sensing receiver achieves a ranging MSE approaching the Cramér-Rao bound (CRB), which notably confirms that our design preserves the target ranging performance even under the non-constant-modulus constellation. Finally, the framework is experimentally validated with our over-the-air OFDM-ISAC testbed.
