Security-Reliability Analysis of AF Full-Duplex Relay Networks Using Self-Energy Recycling and Deep Neural Networks
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články
PubMed
37688073
PubMed Central
PMC10490820
DOI
10.3390/s23177618
PII: s23177618
Knihovny.cz E-zdroje
- Klíčová slova
- deep learning network (DNN), full duplex (FD), intercept probability (IP), outage probability (OP), physical layer security (PLS), self-energy recycling,
- Publikační typ
- časopisecké články MeSH
This paper investigates the security-reliability of simultaneous wireless information and power transfer (SWIPT)-assisted amplify-and-forward (AF) full-duplex (FD) relay networks. In practice, an AF-FD relay harvests energy from the source (S) using the power-splitting (PS) protocol. We propose an analysis of the related reliability and security by deriving closed-form formulas for outage probability (OP) and intercept probability (IP). The next contribution of this research is an asymptotic analysis of OP and IP, which was generated to obtain more insight into important system parameters. We validate the analytical formulas and analyze the impact on the key system parameters using Monte Carlo simulations. Finally, we propose a deep learning network (DNN) with minimal computation complexity and great accuracy for OP and IP predictions. The effects of the system's primary parameters on OP and IP are examined and described, along with the numerical data.
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