Robust Secure Resource Optimization for RIS-Aided Backscatter Communication With HWIs and Channel Uncertainties

Reconfigurable intelligent surface (RIS)-aided backscatter communication (BackCom) has recently attracted a lot of attention due to its potential to enhance energy efficiency (EE) and transmission robustness by reconstructing radio channel environments in a low-power-consumption way. However, most of the existing resource optimization approaches focused on perfect channel state information and ideal hardware conditions, so that the received signals may be distorted by channel uncertainties (e.g., channel estimation errors) and hardware impairments (HWIs) (e.g., distortion noises). To this end, we proposed a more realistic robust secure structure for a RIS-aided BackCom system with the consideration of channel uncertainties, HWIs, and one eavesdropper. Then, we formulate an EE-based maximization resource allocation problem by optimizing the transmit power of base station, the artificial noise power, the RIS's phase shift matrix, and the time slots. To tackle this non-convex problem, an iteration-based robust resource allocation algorithm is proposed by employing the worst-case approach, the variable substitution approach, and the alternating optimization approach. Simulation results demonstrate that the proposed algorithm has 14.84% increase in the EE and 8.78% reduction in outage probability compared to the other algorithms.