Physical layer secret key generation leveraging reciprocity principle of the wireless channel is a promising substitute for traditional cryptography. However, in certain scenarios, the channel measurements extracted by the wireless transceivers are of high correlation but not similar. Therefore, preprocessing channel measurements prior to quantization is highly essential to facilitate successful generation of shared secret keys at the transceivers. In this paper, we put forth the idea of employing discrete wavelet packet transform (DWPT) for dynamic secret key generation in indoor environments. We propose two schemes which are employed at both the transceivers. Proposed method 1 (Prop. method-1) involves fixing the wavelet packet coefficients of selected terminal nodes in the wavelet packet tree to zero and proposed method 2 (Prop. method-2) involves compression of wavelet packet coefficients of selected terminal nodes. The performance of the proposed methods are evaluated using Pearson correlation coefficient, bit disagreement rate (BDR) and NIST randomness tests. Simulation results demonstrate that, Prop. method-1 performs well in terms of cross-correlation, especially when the measurement error variance is high. In contrast to Prop. method-1, Prop. method-2 renders better randomness at the expense of slighty reduced cross-correlation whilst both methods pass all eight NIST randomness tests. The tradeoff between cross-correlation and randomness can be improved owing to the richer signal analysis offered by DWPT. The simulation results are compared against existing works for validating performance of the proposed methods. Simulation results demonstrate that, DWPT based preprocessing is a highly promising solution for successful physical layer secret key generation.

利用无线通道的互惠原理，物理层秘密密钥生成是传统加密技术的有希望的替代方法。但是，在某些情况下，无线收发器提取的信道测量值具有很高的相关性，但并不相似。因此，量化之前的预处理信道测量对于在收发器处成功生成共享密钥非常重要。在本文中，我们提出了使用离散小波包变换（DWPT）在室内环境中动态生成动态密钥的想法。我们提出了两个收发器都采用的两种方案。提议的方法1（提议方法-1）包括将小波包树中的所选终端节点的小波包系数固定为零，而提议的方法2（提议1。方法2）涉及压缩所选终端节点的小波包系数。使用皮尔逊相关系数，比特异议率（BDR）和NIST随机性测试评估了所提出方法的性能。仿真结果表明，Prop。method-1在互相关方面表现良好，尤其是在测量误差方差较大时。与Prop。method-1相反，Prop。method-2呈现出更好的随机性，但互相关性略有降低，而两种方法均通过了所有八项NIST随机性测试。由于DWPT提供了更丰富的信号分析，因此可以改善互相关和随机性之间的权衡。将仿真结果与现有工作进行比较，以验证所提出方法的性能。仿真结果表明，