Cognitive radio (CR), Nonorthogonal multiple access (NOMA), Unmanned aerial vehicle (UAV), RIS, Covert communication
Abstract :
[en] This paper examines a cognitive radio (CR) nonorthogonal multiple access (NOMA) system
in which an unmanned aerial vehicle equipped with a reconfigurable intelligent surface (UAV-RIS) plays
two roles: relaying and friendly jamming. The communication protocol has two phases. The first is an
energy harvesting phase in which the UAV harvests radio frequency energy from a power beacon. A
secondary transmitter (ST) simultaneously sends superimposed signals to secondary receivers (SRs) (a
public SR and a covert SR) via NOMA with the assistance of the UAV-RIS. Then, a UAV warden and
a UAV jammer launch a cooperative attack, in which the first adversary wiretaps the signals from the
ST and UAV-RIS, whereas the second interferes with the SRs to force the ST to increase its transmit
power. For improved secrecy, the UAV-RIS uses its harvested energy to combat the UAV warden. For
this system, the secrecy performance is evaluated on the basis of the concept of covert communication.
In particular, optimization algorithms are employed to maximize the covert SR throughput under outage
probability and security constraints. A deep neural network model is subsequently trained to discover the
relationships between the environmental parameters and optimized parameters to enable rapid adaptation
to environmental conditions.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Vo, Van Nhan ; Faculty of Information Technology, Duy Tan University, Da Nang, Vietnam
Long, Nguyen Quoc; Faculty of Information Technology, Duy Tan University, Da Nang, Vietnam
Dang, Viet-Hung; Faculty of Information Technology, Duy Tan University, Da Nang, Vietnam
Ho, Tu Dac ; Faculty of Information Technology and Electrical Engineering, Department of Information Security and Communication Technology, Norwegian University of Science and Technology -NTNU, Norway
Tran, Hung; College of Technology, DATCOM Lab, Faculty of Data Science and Artificial Intelligence, National Economics University, Hanoi, Vietnam
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