论文标题
针对解调参考信号的顺序异常检测5G NR中的欺骗
Sequential Anomaly Detection Against Demodulation Reference Signal Spoofing in 5G NR
论文作者
论文摘要
在第五代（5G）新无线电（NR）中，将解调参考信号（DMR）用于通道估计，作为物理上行链路共享通道相干解调的一部分。但是，DMRS欺骗对5G NR构成了严重威胁，因为不准确的通道估计会严重降低解码性能。在这种对应关系中，我们建议利用通道的空间稀疏结构来检测DMRS欺骗，这是由于通道的空间稀疏结构发生的事实，如果发生DMRS欺骗，该通道的空间稀疏结构将受到重大影响。我们首先通过解决稀疏特征检索问题来提取通道的空间稀疏结构，然后提出一种顺序稀疏结构异常检测方法来检测DMRS欺骗。在仿真实验中，我们从3GPP标准中利用了群集延迟线模型进行验证。数值结果表明，我们的方法优于基于子空间维度和基于能量探测器的方法。
In fifth generation (5G) new radio (NR), the demodulation reference signal (DMRS) is employed for channel estimation as part of coherent demodulation of the physical uplink shared channel. However, DMRS spoofing poses a serious threat to 5G NR since inaccurate channel estimation will severely degrade the decoding performance. In this correspondence, we propose to exploit the spatial sparsity structure of the channel to detect the DMRS spoofing, which is motivated by the fact that the spatial sparsity structure of the channel will be significantly impacted if the DMRS spoofing happens. We first extract the spatial sparsity structure of the channel by solving a sparse feature retrieval problem, then propose a sequential sparsity structure anomaly detection method to detect DMRS spoofing. In simulation experiments, we exploit clustered delay line based channel model from 3GPP standards for verifications. Numerical results show that our method outperforms both the subspace dimension based and energy detector based methods.
