학술논문

Analyzing Physical-Layer Security of PLC Systems Using DCSK: A Copula-Based Approach
Document Type
Periodical
Source
IEEE Open Journal of the Communications Society IEEE Open J. Commun. Soc. Communications Society, IEEE Open Journal of the. 4:104-117 2023
Subject
Communication, Networking and Broadcast Technologies
Modulation
Internet of Things
Security
Fourth Industrial Revolution
Fading channels
Computational modeling
Mathematical models
Power line communication
physical layer security
secure outage probability
strictly positive secrecy capacity
log-normal distribution
Bernoulli-Gaussian random process
secrecy throughput
Language
ISSN
2644-125X
Abstract
This study analyzes the physical layer security (PLS) performance of a differential chaos shift keying (DCSK) modulation-based Power Line Communication (PLC) system by exploiting the novel Farlie-Gumbel-Morgenstern (FGM) Copula approach. A power line Wyner’s wiretap channel model is investigated, where the main channel and the wiretap channel are assumed to be correlated and Log-normally distributed. The Gamma approximation to the Log-normal distribution is employed to simplify the computation. Concurrently, the PLC channel noise is modeled as a Bernoulli-Gaussian random process. Utilizing a Copula based approach to model the dependence among the correlated PLC channels, the PLS performance of the PLC system is evaluated in terms of the secure outage probability (SOP) and the strictly positive secrecy capacity (SPSC). It is revealed through the asymptotic SOP analysis that the secrecy diversity order depends on the shaping parameter $(m_{\gamma _{M}})$ of the main channel. We also propose an algorithm to maximize the secrecy throughput under SOP constraints. Based on the insights from this analysis, it has been seen that the SOP performance degrades when the value of the dependence parameter $(\theta)$ increases. Also, the secrecy throughput performance improves with a lower optimal threshold value of the signal-to-noise ratio (SNR), $\gamma _{\textrm {th}}$ . Furthermore, some other insightful observations are presented by studying the impact of different parameters such as spreading factor $(\beta)$ , impulsive noise occurrence probability $(p)$ , transmitted power $(P_{T})$ , and impulsive noise index $(K)$ .