Joint Transmit and Reflective Beamformer Design for Secure Estimation in IRS-Aided WSNs

Wireless sensor networks (WSNs) comprise several spatially distributed sensor nodes that communicate over an open radio channel, thereby making the network vulnerable to eavesdroppers (EDs). As a physical layer security approach, intelligent reflecting surface (IRS) technology has recently emerged as an effective technique for security in WSNs. Unlike prior works that do not consider the role of the IRS in facilitating the parameter estimation in WSN, we propose a scheme for joint transmit and reflective beamformer (JTRB) design for secure parameter estimation at the fusion center (FC) in the presence of an ED. To solve the resulting non-convex optimization problem, we develop a semidefinite relaxation (SDR)-based iterative algorithm, which alternately yields the transmit beamformer at each sensor node and the corresponding reflection phases at the IRS, to achieve the minimum mean-squared error (MMSE) parameter estimate at the FC, subject to transmit power and ED signal-to-noise ratio (SNR) constraints. Our simulation results demonstrate robust MSE and security performance of the proposed IRS-based JTRB technique.