A PHY Layer Security Analysis of Uplink Cooperative Jamming-Based Underlay CRNs with Multi-Eavesdroppers

11/28/2019 ∙ by Mounia Bouabdellah, et al. ∙ 0

In this paper, the physical layer security of a dual-hop underlay uplink cognitive radio network is investigated over Nakagami-m fading channels. Specifically, multiple secondary sources are taking turns in accessing the licensed spectrum of the primary users and communicating with a multiantenna secondary base station D through the aid of a multiantenna relay R in the presence of M eavesdroppers that are also equipped with multiple antennas. Among the remaining nodes, one jammer is randomly selected to transmit an artificial noise to disrupt all the eavesdroppers that are attempting to intercept the communication of the legitimate links i.e., S-R and R-D. The received signals at each node are combined using maximal-ratio combining. Secrecy analysis is provided by deriving closed-form and asymptotic expressions for the secrecy outage probability. The impact of several key parameters on the system's secrecy e.g., transmit power of the sources, number of eavesdroppers, maximum tolerated interference power, and the number of diversity branches is investigated. Importantly, by considering two scenarios, namely (i) absence and (ii) presence of a friendly jammer, new insights are obtained for the considered communication system. Especially, we tend to answer to the following question: Can better secrecy be achieved without jamming by considering a single antenna at eavesdroppers and multiple-ones at the legitimate users (i.e., relay and end-user) rather than sending permanently an artificial noise and considering that both the relay and the destination are equipped with a single antenna, while multiple antennas are used by the eavesdroppers? The obtained results are corroborated through Monte Carlo simulation and show that the system's security can be enhanced by adjusting the aforementioned parameters.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.