Physical-layer security enhancement in wireless sensor networks through artificial noise optimization

Ensuring network security is of utmost importance, especially in wireless sensor networks (WSNs), where the confidentiality of data is at risk due to eavesdropping. This paper introduces an artificial-noise-aided secure communication scheme for WSNs. This scheme comprises numerous sensor nodes, the sink, a friendly jammer, and an eavesdropper. The primary aim is to enhance the secrecy rate of the network by optimizing the jamming power. The friendly jammer plays a crucial role in degrading the wiretap channel between the sensor nodes and the eavesdropper. The optimization process revolves around maximizing the secrecy rate, while carefully managing the jamming power to prevent any negative impact on the main transmission link between the sink node and the sensor nodes. Due to the nonconvexity of the secrecy rate problem, the convex approximation-based algorithm is recommened to get a safe convex approximation of the original solution. To address this optimization problem, an iterative algorithm based on quadratic transformation is proposed. Afterwards, the optimum jamming power to achieve high security is obtained. The simulation outcomes underscore the dual impact of the jammer in WSNs. The jammer diminishes the eavesdropper channel. Unfortunately, it introduces interference that consequently affects the security enhancement. In response, we concentrate on the optimization of jamming power. The proposed scheme consistently elevates secrecy rates across a spectrum of eavesdropper positions, adeptly addressing worst-case scenarios. Notably, the algorithm showcases resilience across diverse node distributions.