Generative Adversarial Network Assisted Power Allocation for Cooperative Cognitive Covert Communication System

Liao, Xiaomin; Si, Jiangbo; Shi, Jia; Li, Zan; Ding, Haiyang

doi:10.1109/lcomm.2020.2988384

Cited by 38 publications

(16 citation statements)

References 14 publications

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“…Liao et al proposed an algorithm for the instant network communication system based on Bernoulli matrix. The results show that the algorithm can reduce the local feature dislocation recognition problem in instant network communication system, but it also reduces the recognition accuracy [ 15 ]. In order to improve the accuracy, Ma et al put forward the optimization model of the instant network communication system based on ant colony algorithm and particle swarm algorithm.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Construction and 3D Simulation of Virtual Animation Instant Network Communication System Based on Convolution Neural Networks

2021

Computational Intelligence and Neuroscience

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In recent years, great progress has been made in 3D simulation modeling of instant network communication system, such as the application of virtual reality technology and 3D virtual animation online modeling technology. Facing the increasing demand of different industries, how to build an instant network communication system for 3D virtual animation has become a research hotspot. On this basis, the construction method of fast instant network communication system based on convolutional neural network and fusion morphological 3D simulation model is studied. This paper analyzes the research status of instant network communication system. The experiment optimizes and improves the shortcomings of the current research hotspot of virtual animation instant network communication system and takes the morphological 3D simulation model fusion as the core for in-depth optimization. Finally, the experimental results show that the fusion morphological 3D simulation model can reconstruct the standard 3D virtual animation model according to different needs and can quickly model the optimization strategy according to the local differences of different animations. The response accuracy of the network communication system reaches 97.7%.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Construction and 3D Simulation of Virtual Animation Instant Network Communication System Based on Convolution Neural Networks

2021

Computational Intelligence and Neuroscience

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“…It is extremely difficult for traditional approaches, such as convex optimization, to solve the joint optimization problem of UAV's trajectory and transmit power when missing the detection threshold and full channel information. By contrast, modeldriven generative adversarial network (MD-GAN) approach has become a new research trend to solve the optimization problem with limited priori information in the application of artificial intelligence [30,31], and it is able to provide the feasibility and effectiveness for our UAV jammer aided cognitive radio system under non-ideal scenarios. Motivated by the above, in this paper we commence a pioneer work on blending the advantages of the MD-GAN and UAV jamming for covert communications.…”

Section: B Motivations and Contributionsmentioning

confidence: 99%

“…On the other hand, Problem (11) can be seen as a game between a legitimate user (the UAV) and a warden (the Eve) in covert communication, and can be solved by a newly emerging machine learning method, namely GAN [31]. Basically, a GAN model consists of two modules, a generator as the legitimate user to generate a promising solution and a discriminator as the warden to discriminate the existence of covert message.…”

Section: Problem Formulationmentioning

confidence: 99%

MD-GAN-Based UAV Trajectory and Power Optimization for Cognitive Covert Communications

Liao

Shi

et al. 2022

IEEE Internet Things J.

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This paper investigates the covert performance for an unmanned aerial vehicle (UAV) jammer assisted cognitive radio network. In particular, the covert transmission of secondary users can be effectively protected by UAV jamming against the eavesdropping. For practical consideration, the UAV is assumed to only know certain partial channel distribution information (CDI), whereas not to know the detection threshold of eavesdropper. For this sake, we propose a model-driven generative adversarial network (MD-GAN) assisted optimization framework, consisting of a generator and a discriminator, where the unknown channel information and the detection threshold are learned weights. Then a GAN based joint trajectory and power optimization (GAN-JTP) algorithm is developed to train the MD-GAN optimization framework for covert communication, which results in the joint solution of UAV's trajectory and transmit power to maximize the covert rate and the probability of detection errors. Our simulation results show that, the proposed GAN-JTP with a rapid convergence speed can attain near-optimal solutions of UAV's trajectory and transmit power for the covert communication.

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“…Covert transmission can protect confidential information from detection and can be used in systems with high security requirements, such as finance, national security, and military. There are many papers focusing on covert transmission [20]- [23]. However, few works have investigated IRS-aided covert transmission.…”

Section: Introductionmentioning

confidence: 99%

Covert Transmission Assisted by Intelligent Reflecting Surface

Zhao

et al. 2020

Preprint

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Covert transmission is studied for an intelligent reflecting surface (IRS) aided communication system, where Alice aims to transmit messages to Bob without being detected by the warden Willie.Specifically, an IRS is used to increase the data rate at Bob under a covert constraint. For the considered model, when Alice is equipped with a single antenna, the transmission power at Alice and phase shifts at the IRS are jointly optimized to maximize the covert transmission rate with either instantaneous or partial channel state information (CSI) of Willie's link. In addition, when multiple antennas are deployed at Alice, we formulate a joint transmit beamforming and IRS phase shift optimization problem to maximize the covert transmission rate. One optimal algorithm and two low-complexity suboptimal algorithms are proposed to solve the problem. Furthermore, for the case of imperfect CSI of Willie's link, the optimization problem is reformulated by using the triangle and the Cauchy-Schwarz inequalities.The reformulated optimization problems are solved using an alterative algorithm, semidefinite relaxation (SDR) and Gaussian randomization techniques. Finally, simulations are performed to verify our analysis.The simulation results show that an IRS can degrade the covert transmission rate when Willie is closer to the IRS than Bob.

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Generative Adversarial Network Assisted Power Allocation for Cooperative Cognitive Covert Communication System

Cited by 38 publications

References 14 publications

[Retracted] Construction and 3D Simulation of Virtual Animation Instant Network Communication System Based on Convolution Neural Networks

[Retracted] Construction and 3D Simulation of Virtual Animation Instant Network Communication System Based on Convolution Neural Networks

MD-GAN-Based UAV Trajectory and Power Optimization for Cognitive Covert Communications

Covert Transmission Assisted by Intelligent Reflecting Surface

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