Enhancing Physical Layer Security of URLLC using Artificial Noise in Full-Duplex Cooperative NOMA

In this paper, we propose enhancing physical layer security (PLS) of ultra-reliable low latency communication (URLLC) in a full-duplex cooperative non-orthogonal multiple access (FD-CNOMA) based Internet of Things (IoT) network. We analyze the PLS performance of a two-user FD-CNOMA system, where a source node transmits the short packet URLLC information to a near user and a far cell-edge user in the presence of an external eavesdropper. To ensure the security and reliability of URLLC signal transmission, the near user is utilized as a cooperative relay for transmitting the information intended for the far user, and also transmits an artificial noise (AN) signal to mitigate the impact of eavesdropping. An approximate closed-form expression of the average secure block error rate (SBLER) and the average secrecy throughput (AST) of the legitimate users under eavesdropping is derived. The analytical framework presented in this work considers the URLLC signal transmission with and without AN signal while evaluating the impact of residual self-interference (RSI) at the relay node on the PLS performance of the FD-CNOMA system. Thus, to improve the PLS performance and maximize the system AST, we optimize the URLLC blocklength and power allocation coefficient (PAC) at the source. The numerical and simulation results validate the proposed analytical framework and demonstrate a significant improvement of average SBLER and overall system AST (SAST) using AN-assisted URLLC signal transmission in the FD-CNOMA system.