IRS-Based Symbiotic Radio Systems: Covertness Performance Analysis and Optimization
Zhen Ming Xu, Manlin Wang, Bin Xia, Jiangzhou Wang · IEEE Internet of Things Journal · 2025
Intelligent reflecting surface (IRS) based symbiotic radio (SR) technology offers a promising approach to enhance Internet of Things (IoT) connectivity. Despite its potential, current simple implementations face significant security challenges that could undermine the reliability of IoT connectivity. To tackle this security issue, this paper introduces a novel model for covert SR transmission that employs joint passive and active beamforming strategies to counteract risks from multiple warders. In this model, the IRS acts as a secondary transmitter, backscattering binary phase shift keying signals. The system is categorized into two operational modes: parasitic SR (PSR) and commensal SR (CSR), based on the synchronization requirements between primary and secondary signals. A comprehensive analysis of the bit error rate for each mode is conducted, and the Kullback-Leibler divergence is leveraged to measure system covertness, establishing a tractable covertness constraint for subsequent optimization. To address the effects of imperfect channel state information on beamforming performance, a robust joint beamforming algorithm is proposed. Our results show that this algorithm outperforms existing baselines. Particularly in CSR mode, high reliability and strong covertness can be achieved with a minimal number of IRS reflecting elements, providing a cost-effective solution for communication security in IoT applications.