A probing model of secret key generation based on channel autocorrelation function
Enjun Xia, HU Bin-jie, Shen Qiaoqiao · China Communications · 2024
Secret key generation (SKG) is a promising solution to the problem of wireless communications security. As the first step of SKG, channel probing affects it significantly. Although there have been some probing schemes, there is a lack of research on the optimization of the probing process. This study investigates how to optimize correlated parameters to maximize the SKG rate (SKGR) in the time-division duplex (TDD) mode. First, we build a probing model which includes the effects of transmitting power, the probing period, and the dimension of sample vectors. Based on the model, the analytical expression of the SKGR is given. Next, we formulate an optimization problem for maximizing the SKGR and give an algorithm to solve it. We conclude the SKGR monotonically increases as the transmitting power increases. Relevant mathematical proofs are given in this study. From the simulation results, increasing appropriately the probing period and the dimension of the sample vector could increase the SKGR dramatically compared to a yardstick, which indicates the importance of optimizing the parameters related to the channel probing phase.