无人机辅助OFDM系统中基于视距感知的信道估计
LoS Sensing-based Channel Estimation in UAV-Assisted OFDM Systems
AI总结：
针对无人机辅助OFDM系统，本文提出一种基于视距感知的信道估计方法，通过检测视距路径并设计专用阈值对最小二乘估计去噪，有效提升了信道估计精度和鲁棒性。
摘要：
在无人机（UAV）辅助的正交频分复用（OFDM）系统中，视距（LoS）路径因其高存在概率而具有的潜在优势尚未得到充分利用，从而阻碍了信道估计（CE）精度的提升。受感知通信一体化（ISAC）思想的启发，本文提出了一种视距感知方法，旨在检测视距路径的存在性。利用视距路径检测获得的先验信息，分别针对视距和非视距（NLoS）场景提出了可分辨路径的检测阈值。通过采用这些专门设计的检测阈值，对经典最小二乘（LS）信道估计进行去噪处理，从而提高了信道估计精度。仿真结果验证了所提方法在提升信道估计精度方面的有效性，并证明了其对参数变化的鲁棒性。
英文摘要：
In unmanned aerial vehicle (UAV)-assisted orthogonal frequency division multiplexing (OFDM) systems, the potential advantage of the line-of-sight (LoS) path, characterized by its high probability of existence, has not been fully harnessed, thereby impeding the improvement of channel estimation (CE) accuracy. Inspired by the ideas of integrated sensing and communication (ISAC), this letter develops a LoS sensing method aimed at detecting the presence of LoS path. Leveraging the prior information obtained from LoS path detection, the detection thresholds for resolvable paths are proposed for LoS and Non-LoS (NLoS) scenarios, respectively. By employing these specifically designed detection thresholds, denoising processing is applied to classical least square (LS) CE, thereby improving the CE accuracy. Simulation results validate the effectiveness of the proposed method in enhancing CE accuracy and demonstrate its robustness against parameter variations.
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