Robust Secure Resource Allocation for MISO-Based SR Systems With HWIs and Channel Uncertainties

Chuan Liu, Pei Liu, Junming Wu, Hao Deng, Fengxia Han, Yongjun Xu

Abstract: Resource allocation (RA) has been considered as a key technique to achieve the optimal system performance in symbiotic radio (SR) systems by optimizing system parameters. However, most of the existing works only consider the ideal hardware conditions or perfect channel information, where the system performance of the above algorithms may be degraded under imperfect channel state information (CSI) (e.g., channel estimation errors) and unideal hardware conditions (e.g., distortion noises). To improve transmission robustness and information security, in this paper, we study the robust secure RA problem for a multiple-input single-output (MISO) SR system under channel uncertainties and hardware impairments (HWIs) with an eavesdropper (Eve). The robust RA problem with bounded channel uncertainties is formulated to maximize the total energy efficiency (EE) of the system under the minimum energy-harvesting constraint of each backscatter device (BD), the maximum transmit power constraint of the primary base station (PBS), the minimum secrecy rate of each BD, the decoding constraint, as well as the reflection coefficient constraint. To address the nonconvex optimization problem, the original robust RA problem with the infinite constraints is converted into a deterministic one via a worst case approach. Then, the objective function is transformed into a nonfractional form using Dinkelbach’s method. After that, the above problem is converted into a convex problem based on $S$ -Procedure and the eigenvalue decomposition approach, and an iterative-based robust secure RA algorithm is proposed via an alternating optimization principle. Simulation results demonstrate that the proposed algorithm has lower outage probabilities and higher EE compared to the nonrobust algorithm and the RA algorithm without HWIs.

External IDs:dblp:journals/iotj/LiuLWDHX25