Pilot-aided codebook-based non-orthogonal artificial noise for secrecy capacity enhancement
Recent findings show that orthogonal artificial noise (AN) suffers from limited design flexibility owing to constraints on channel degrees of freedom. Non-orthogonal artificial noise (NORAN) has been adopted in relay-assisted networks including UAV and IRS systems; however, a systematic analytical characterization of secrecy capacity (SC) within NORAN-enabled frameworks is still missing. This paper investigates the convexity behavior of the SC function under NORAN, revealing that under particular transmit power conditions the SC function becomes convex, thereby degrading secrecy performance and making NORAN ineffective. To resolve this issue, we put forward a pilot-aided codebook-based NORAN approach, named PCAN. In this scheme, pilot signals are exploited to establish a shared codebook that permits the legitimate receiver to cancel the artificial noise, thus restoring SC performance to a level comparable with that of conventional AN. Power allocation strategies for PCAN are studied for both perfect and imperfect channel state information (CSI) scenarios.