With the continuous proliferation of wireless communication technologies and the ubiquity of smart devices, the demand for seamless connectivity is escalating. This necessitates secure, energy-efficient, and high-performance communication systems. Conventional security techniques, typically based on cryptography or active jamming, often impose excessive computational or energy burdens, making them unsuitable for next-generation networks. To address these challenges, this thesis investigates the design and optimization of low-complexity and energy-efficient intelligent reflecting surface (IRS)-assisted backscatter communication systems, aiming to achieve secure and reliable communications with significantly reduced computational and hardware overhead.
This research represents a shift from reactive security paradigms toward a proactive, design-oriented approach, leveraging the capabilities of IRS technology. The thesis contributes three distinct yet complementary system architectures. The first focuses on IRS-backscatter designs for hybrid confidential information and artificial noise transmission, ensuring robustness against eavesdropping. The second extends this paradigm to simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) architectures, enabling secure indoor multi-user communications through simultaneous reflection and transmission control. The third explores IRS-backscatter enabled downlink systems under radar communication coexistence (RCC), bridging secure communication and integrated sensing, and advancing the vision of intelligent dual-functional wireless networks.
Extensive simulations are conducted to evaluate these systems, demonstrating significant improvements across secrecy rate, energy efficiency, computational complexity, and scalability. The backscatter-based designs prove highly energy-efficient and resistant to passive eavesdropping, while the STAR-RIS and RCC frameworks show strong potential for secure multi-user connectivity and spectrum-efficient coexistence with radar sensing.
In paving the way for future wireless networks, this thesis contributes critical building blocks toward realizing an intelligent wireless ecosystem capable of proactively countering security threats while optimizing performance. The findings hold important implications for sixth-generation (6G) and beyond, where embedding intelligence into the propagation environment will be essential to meet the rigorous demands of emerging applications.
