Artificial Noise Aided Secure Communications for Cooperative NOMA Networks

Cao, Zhen; Ji, Xiaodong; Wang, Jue; Wang, Wei; Cumanan, Kanapathippillai; Ding, Zhiguo; Dobre, Octavia A.

doi:10.1109/tccn.2021.3130979

Cited by 11 publications

(5 citation statements)

References 55 publications

(144 reference statements)

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“…Additionally, three different cases of self-interference (SI) signal in FD mode were adopted to investigate the impact of SI cancellation on system secure performance. In [24], one source established communication directly with a multi-antenna near-user, while the source used multiple FD relays to communicate with the distant user in the case of passive Eves. To solve this wiretapping problem, a new FD-based two-stage AN scheme was proposed, where AN is not only an interference signal to prevent eavesdropping but also acts as a secret key to enhance the confidentiality of the distant user.…”

Section: Related Workmentioning

confidence: 99%

“…Compared with the traditional upper-layer security technology, physical layer security (PLS) does not need to consume a lot of communication resources or infrastructure to share encryption technology between legitimate users, which is more suitable against wiretapping attacks in IoT networks [17]. Therefore, various PLS technology adopted by the NOMA system, such as relay-aided diversity and cooperative jamming, has gradually attracted widespread attention from academia and is regarded as a research hotspot to achieve massive connectivity and secure transmission [15][16][17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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Enhancing Physical Layer Security of Cooperative Nonorthogonal Multiple Access Networks via Artificial Noise

Jiang,

Gao,

et al. 2023

Electronics

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The massive connectivity requirement and security issues have become major factors restricting the further development of the Internet of Things. Nonorthogonal multiple access (NOMA) can be combined with physical layer security (PLS) to achieve massive connectivity and secure transmission. This article investigates the PLS performance for a downlink communication system over Nakagami-m fading channels, with full-duplex (FD) cooperative NOMA transmission aided by artificial noise (AN). While direct communication is built between the base station and two NOMA users, the strong user is employed as an FD relay as well as the jammer to enhance the PLS of the legitimate transmission in the presence of a passive eavesdropper (Eve). Closed-form analytical expressions in terms of the outage probability of the legitimate users and the intercept probability of Eve are derived to evaluate the security–reliability trade-off (SRT) of the proposed scheme. Monte Carlo simulations are provided to validate the veracity of the theoretic analyses and illustrate that the proposed scheme is superior in terms of SRT to the benchmark schemes in the low SNR region. Furthermore, the results reveal that the SRT performance of the two NOMA users can be enhanced through a proper AN-bearing ratio and power allocation optimization.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing Physical Layer Security of Cooperative Nonorthogonal Multiple Access Networks via Artificial Noise

Jiang,

Gao,

et al. 2023

Electronics

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“…The wired forward link is not flexible enough in deployment. Some urban areas may not be suitable for laying wired links [10,11]. With the increase of wired forward links, the network complexity of the forward link will increase exponentially.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Reflecting Surface Aided Cloud Access Networks with Federated Learning

Fan¹,

Ou²,

et al. 2023

EAI Endorsed Trans Mob Com Appl

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Compared with traditional cellular network architecture, cloud access network has some significant advantages in spectrum utilization, energy consumption and network construction cost. However, a high-quality forward link is required between the baseband processing unit pool and remote radio head (RRH) in the cloud access network, which results in limited RRH deployment and affects user access link transmission and coverage. To solve this issue, this paper introduces the intelligent reflector technology into the cloud access network as a solution with low energy consumption, low cost and easy deployment to deal with the existing bottlenecks. Firstly, an efficient channel information acquisition strategy based on federated learning is designed for the smart reflector to enhance the user access link, so as to achieve a compromise between the channel estimation accuracy and cost. On this basis, a robust beamforming design and optimization method of the compression mechanism of the forward link are proposed for the smart reflector to enhance the user access link and the wireless forward link, so as to improve the system transmission performance. Finally, we explore the joint resource allocation method of intelligent reflector assisted cloud access network, and improve the system energy efficiency through the collaborative configuration of intelligent reflector and cloud access network communication resources. The research of this paper will provide an important theoretical basis for the application of intelligent reflectors in cloud access networks, especially for the federated learning.

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“…With the increasing scarcity of frequency and harmonic resources, the exploitation of airspace resources has become an effective way to achieve and enhance covert communications [11,12]. Singleantenna transceivers have extremely limited airspace freedom, which makes it difficult to reconcile the conflict between the system's frequency-harmonic efficiency and its stealthiness [13,14]. Another implementation of MIMO, distributed node collaboration, can also help improve covert communications by using collaborating nodes to relay signals or to take turns for the target signal transmission.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Reflecting Surface Aided Secure Communication with Federated Learning

Lai

Tang

et al. 2023

EAI Endorsed Trans Mob Com Appl

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Applying federated learning into the covert communication can not only ensure the communication reliability, but also reduce the probability of enemy detection. The use of airspace resources is an effective way to achieve covert communication. However, most of the existing works on the airspace covert communication represented by MIMO need to adapt to the channel state and cannot improve the channel, resulting in the performance bottleneck of covert communication. The intelligent reflective surface (IRS) provides a new perspective for the covert communication by flexibly adjusting the reflection phase shift of the incident signal and intelligently configuring the wireless channel. However, the potential of IRS in the covert communication is far from being fully exploited. To solve this issue, this paper firstly performs a comprehensive literature review on the secure communication with the aid of federated learning, and then gives some challenges on the secure communication in poor channel state. In further, this paper provides some solutions to the challenges on the secure communication, where some results are provided to show the advantages. The research results have important theoretical and practical significance for forming a new research paradigm of airspace intelligent and controllable covert communication and promoting the application and popularization of covert communication in various fields of security.

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Artificial Noise Aided Secure Communications for Cooperative NOMA Networks

Abstract: reveal that the SRT of the near-user and far-user can be improved by increasing the number of antennas at the near-user and the number of relays.

Cited by 11 publications

References 55 publications

Enhancing Physical Layer Security of Cooperative Nonorthogonal Multiple Access Networks via Artificial Noise

Enhancing Physical Layer Security of Cooperative Nonorthogonal Multiple Access Networks via Artificial Noise

Intelligent Reflecting Surface Aided Cloud Access Networks with Federated Learning

Intelligent Reflecting Surface Aided Secure Communication with Federated Learning

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