基于信道特征高精度提取的空地信道密钥量化

针对无人机空地信道，基于空间期望最大化算法(SAGE)对信道特征参数进行高精确度估计。在提取了多径时延、多径功率等空地信道小尺度衰落特征后，利用均匀量化和非均匀量化方法，对实测数据的主径功率、主径-多径功率差开展无线信道密钥量化。分别针对起飞和巡航场景分析了密钥的量化效率、随机性以及算法运行时间等指标，并与基于大尺度特征的密钥量化结果进行比较。密钥量化效率结果表明：基于非均匀量化优于均匀量化；基于信道特征高精确度估计的量化方法优于传统基于大尺度特征的量化；起飞场景下的量化优于巡航场景的量化。密钥随机性测试结果表明本次量化所获得的密钥都具有较好的随机性；算法运行时间结果则表明不同量化方法的运行时间差异较小。因此基于高精确度提取的2种量化方法复杂度较低。

Air-to-ground wireless channel key quantization based on high-precision extraction of channel characteristics

Aiming at the UAV air-ground channel, based on the Space-Alternating Generalized Expectation-maximization(SAGE), the channel characteristic parameters are estimated with high precision, and the small-scale fading characteristics of the air-ground channel such as multipath delay and multipath power are extracted. Then, using uniform quantization and non-uniform quantization methods, the wireless channel key quantization is carried out on the main path power and the main path-multipath power difference of the measured data. The quantification efficiency, randomness, and algorithm running time of the key are analyzed for takeoff and cruise scenarios respectively, and compared with the key quantification results based on large-scale features. The key quantization efficiency results show that the non-uniform guard quantization is superior to the uniform guard quantization; the quantization method based on high-precision estimation of channel characteristics is better than traditional quantization based on large-scale features; and the quantization in the take-off scenario is better than that in the cruise scenario. The results of the performance test show that the keys obtained in these quantizations have good randomness; the running time difference of different quantization methods is small, therefore, the two quantization methods based on high-precision extraction bear low complicity.