Physical Layer Key Generation Scheme for MIMO System Based on Feature Fusion Autoencoder

Recently, the use of wireless channel state information (CSI) to generate encryption keys in the physical layer has gained significant attention from researchers. Unlike classical cryptography, this approach relies on the variability of the wireless channel, channel reciprocity, and spatial decorrelation to ensure security, making it more lightweight and providing strong randomness. This article proposes a physical layer key generation scheme for wireless LAN MIMO systems based on feature fusion autoencoder (FFAEncoder) to address the issue of a high key disagreement rate (KDR). Our approach involves extracting amplitude and phase features separately, fusing them through multiplication operator in a neural network, and using an autoencoder to extract common features. The proposed scheme was evaluated on multiple data sets in different real-world scenarios, and it was found that the transmitter and receiver codeword's mean squared error (MSE) and mean absolute error (MAE) were smaller than those of the current models, indicating better key generation performance. Additionally, the proposed scheme's KDR was smaller, with a decay rate faster than that of the other two models in the same environment, and the primary key bits were 1/2 and 1/3 that of the other models, respectively, as the signal-to-noise ratio (SNR) increased.

Automated summary

Recently, there has been significant attention from researchers in using wireless channel state information (CSI) for generating encryption keys in the physical layer. This approach relies on the variability of the wireless channel, channel reciprocity, and spatial decorrelation to ensure security, making it lightweight and providing strong randomness. The proposed scheme in this article utilizes a feature fusion autoencoder (FFAEncoder) to address the high key disagreement rate (KDR) in wireless LAN MIMO systems, achieving better key generation performance than current models.