Enhancing Secrecy Performance Using Fountain Codes and NOMA under Joint Cooperative Jamming Technique and Intelligent Reflective Surface

초록

Ensuring content security and copyright protection is a critical concern in wireless communication networks. Furthermore, the emergence of services demanding high-band width and very low delay such as online Games, extended reality (XR), Metaverses, etc., Non-Orthogonal Multiple Access (NOMA) is a technology with the potential to enhance the spectral efficiency of fifth-generation (5G) wireless network and beyond. Hence, this paper studies a NOMA-based downlink system that employs intelligent reconfigurable surfaces (IRS) and operates in a physical-layer security environment. Our study also incorporates the utilization of Fountain codes (FCs), all while contending with the presence of a malicious eavesdropper. Furthermore, a cooperative jamming technique is employed to degrade the quality of the eavesdropping channel. The main contribution of this paper is to derive precise closed-form expressions of outage probability (OP), energy efficiency (EE), intercept probability (IP), and average secrecy rate (ASR) for the proposed system. We also develop a Deep Neural Network (DNN) model to evaluate OP, IP, ASR and the average number of time slots (ATS). Subsequently, Monte Carlo simulations are presented as a means to validate the theoretical findings. The simulation results yield the following insights: i) Their primary purpose is to validate the analytical formulas. ii) This research significantly contributes to deepening our understanding of IRS-NOMA systems, providing a foundation for future investigations into practical implementations. iii) We investigate the optimal power allocation factors within the IRS-NOMA framework, offering valuable insights into designing IRS-NOMA systems to achieve reliable and secure communication. iv) The results illustrate the superior performance of IRS-NOMA in comparison to the conventional IRS-Orthogonal Multiple Access (OMA) method. Authors

키워드