Improving Physical-Layer Security for Cognitive Networks via Artificial Noise-Aided Rate Splitting
P.X. Yan, Wei Duan, Qiang Sun, Guoan Zhang, Jiayi Zhang, Pin‐Han Ho
Abstract
This letter investigates secrecy performance for cognitive transmissions, where a secondary user (SU) shares same spectrum with a primary user (PU) simultaneously ensuring the Quality of Service (QoS) of primary transmissions. Additionally, an eavesdropper (Eve) overhears cognitive transmissions from SU to base station (BS). To against eavesdropping attacks, a novel artificial noise-aided rate splitting (ANRS) scheme is proposed, where PU emits artificial noise to confuse Eve and SU adopts rate splitting (RS). The numerical results of secrecy outage probability indicates that the ANRS scheme achieves better secrecy performance than that of AN without RS (ANWRS) and of RS without AN (RSWAN) schemes.