发表机构
Istanbul Medipol University（伊斯坦布尔医学波利大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对5G NR TDD V2X链路，提出双向CFO分离方法，利用DL与UL的PT-RS获取CFO估计值，实现径向速度估计，可协同RTT定位，适用于V2X ISAC场景。
AI 中文摘要
在正交频分复用（OFDM）链路上实现高精度速度估计颇具挑战性，因为多普勒频移与本地振荡器（LO）漂移对观测到的载波频率偏移（CFO）的影响方式相同。本文针对路边gNB/TRP与车载用户设备（UE）之间的1号频率范围（FR1）时分双工（TDD）Uu链路，提出一种双向CFO分离方法：分别从物理下行共享信道和物理上行共享信道的相位跟踪参考信号（PT-RS）获取下行链路（DL）和上行链路（UL）的CFO估计值，二者之和可分离出径向多普勒并提取径向速度，二者之差则可恢复相对LO偏移。该方法采用闭式形式计算，无需任何迭代处理，仅需利用上行链路反馈的紧凑标量CFO报告即可实现，可与新空口（NR）往返时间（RTT）定位事件协同调度，以实现测距测量与速度估计同步进行。本文推导了理想情况下的克拉美-罗下界（CRLB），证明线性相位斜率估计器在高信噪比下可达到该下界，评估了其对到达角不确定性和多径的敏感性，并讨论了射频链失配问题。最终的链路级实现符合NR PDSCH/PUSCH PT-RS流程，适用于网络辅助的车万物联网（V2X）集成感知与通信（ISAC）场景。
英文摘要
High-accuracy velocity estimation over orthogonal frequency division multiplexing (OFDM) links is challenging because Doppler shifts and local oscillator (LO) drift contribute the same way to the observed carrier frequency offset (CFO). We propose a bidirectional CFO separation method for a frequency range-1 (FR1) time division duplex (TDD) Uu link between a roadside gNB/TRP and a vehicle user equipment (UE). Downlink (DL) and uplink (UL) CFO estimates are obtained from the physical downlink and uplink shared channel phase tracking reference signals (PT-RS), respectively, their sum isolates the radial Doppler and allow for the extraction of the radial velocity, while their difference recovers the relative LO offset. The estimates are obtained in closed form, without any iterative processing, using only a compact scalar CFO report fed back on the UL, the method can be co-scheduled with an new radio (NR) round trip time (RTT) positioning event to enable simultaneous ranging measurements along velocity estimates. We derive an idealized Cramér-Rao lower bound (CRLB), show that a linear phase slope estimator attains it at high signal to noise ratio, evaluate sensitivity to angle of arrival uncertainty and multipath, and discuss RF chain mismatch. The resulting link level implementation is aligned with NR PDSCH/PUSCH PT-RS procedures and is suitable for network assisted vehicle to everything (V2X) integrated sensing and communication (ISAC).
