Research Article
Intercept Probability Analysis of Cooperative Cognitive Networks Using Fountain Codes and Cooperative Jamming
@ARTICLE{10.4108/eai.26-1-2021.168229, author={Tran Trung Duy and Le Chu Khan and Nguyen Thanh Binh and Nguyen Luong Nhat}, title={Intercept Probability Analysis of Cooperative Cognitive Networks Using Fountain Codes and Cooperative Jamming}, journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems}, volume={8}, number={26}, publisher={EAI}, journal_a={INIS}, year={2021}, month={1}, keywords={Fountain Codes, underlay cognitive radio networks, physical-layer security, cooperative jamming, intercept probability}, doi={10.4108/eai.26-1-2021.168229} }
- Tran Trung Duy
Le Chu Khan
Nguyen Thanh Binh
Nguyen Luong Nhat
Year: 2021
Intercept Probability Analysis of Cooperative Cognitive Networks Using Fountain Codes and Cooperative Jamming
INIS
EAI
DOI: 10.4108/eai.26-1-2021.168229
Abstract
This paper evaluates intercept probability (IP) of a cooperative cognitive radio network. Using Fountain codes, a secondary source continuously generates encoded packets, and sends them to secondary destination and relay nodes that attempt to receive a sufficient number of the encoded packets for recovering the source data. If the relay can sufficiently collect the packets before the destination, it replaces the source to transmit the encoded packets to the destination. Also in the secondary network, a passive eavesdropper attempts to illegally receive the packets sent by the source and relay nodes, and if it can accumulate enough encoded packets, the source data is intercepted. To enhance secrecy performance, in terms of IP, a cooperative jammer is used to transmit noises on the eavesdropper. We also propose a simple transmit power allocation method for the secondary transmitters such as source, relay and jammer so that outage performance of a primary network is not harmful. We derive an exact closed-form expression of IP over Rayleigh fading channel, and verify it by performing Monte-Carlo simulations.
Copyright © 2021 Tran Trung Duy et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.