53 research outputs found
The Role of Physical Layer Security in Satellite-Based Networks
In the coming years, 6G will revolutionize the world with a large amount of
bandwidth, high data rates, and extensive coverage in remote and rural areas.
These goals can only be achieved by integrating terrestrial networks with
non-terrestrial networks. On the other hand, these advancements are raising
more concerns than other wireless links about malicious attacks on
satellite-terrestrial links due to their openness. Over the years, physical
layer security (PLS) has emerged as a good candidate to deal with security
threats by exploring the randomness of wireless channels. In this direction,
this paper reviews how PLS methods are implemented in satellite communications.
Firstly, we discuss the ongoing research on satellite-based networks by
highlighting the key points in the literature. Then, we revisit the research
activities on PLS in satellite-based networks by categorizing the different
system architectures. Finally, we highlight research directions and
opportunities to leverage the PLS in future satellite-based networks
GWO-BP neural network based OP performance prediction for mobile multiuser communication networks
The complexity and variability of wireless channels makes reliable mobile multiuser communications challenging. As a consequence, research on mobile multiuser communication networks has increased significantly in recent years. The outage probability (OP) is commonly employed to evaluate the performance of these networks. In this paper, exact closed-form OP expressions are derived and an OP prediction algorithm is presented. Monte-Carlo simulation is used to evaluate the OP performance and verify the analysis. Then, a grey wolf optimization back-propagation (GWO-BP) neural network based OP performance prediction algorithm is proposed. Theoretical results are used to generate training data. We also examine the extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), BP neural network, and wavelet neural network methods. Compared to the wavelet neural network, LWLR, SVM, BP, and ELM methods, the results obtained show that the GWO-BP method provides the best OP performance prediction
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