Joint Buffer-Aided Hybrid-Duplex Relay Selection and Power Allocation for Secure Cognitive Networks With Double Deep Q-Network

Huang, Chong; Chen, Gaojie; Gong, Yu; Han, Zhu

doi:10.1109/tccn.2021.3063525

Cited by 23 publications

(6 citation statements)

References 39 publications

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“…With the development of deep learning (DL), DL has been applied to wireless relay networks [ 33 , 34 , 35 ]. A large number of researchers have started to use deep learning to study buffer-aided relay selection [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ]. The authors in [ 36 ] model the buffer-aided relay selection as a multi-classification problem and uses a deep neural network (DNN) to predict the suitable link to transmit the signals.…”

Section: Related Workmentioning

confidence: 99%

“…On this basis, the authors in [ 40 , 41 ] realized reliable communications for IoTs [ 40 ] and CRNs [ 41 ] by using the DQL-based buffer-aided relay selection schemes. The authors in [ 40 , 41 ] extend their work further and use the proposed DQL-based buffer-aided relay selection scheme to realize reliable and secure communications in CRNs [ 42 , 43 ].…”

Section: Related Workmentioning

confidence: 99%

“…DQL makes it possible to achieve reliable and secure communications using buffer-aided relay selection. However, the works in [ 42 , 43 ] use DQL to address the issue of power allocation (PA) to achieve reliable and secure communications and they did not consider possible eavesdroppers in the network. Therefore, this paper explores how to achieve reliable and secure communications using only a DQL-based buffer-aided relay selection scheme in the more common two-hop wireless relay networks rather than CRNs.…”

Section: Related Workmentioning

confidence: 99%

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Deep Q-Learning-Based Buffer-Aided Relay Selection for Reliable and Secure Communications in Two-Hop Wireless Relay Networks

Zhang

Liao

et al. 2023

Sensors

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This paper investigates the problem of buffer-aided relay selection to achieve reliable and secure communications in a two-hop amplify-and-forward (AF) network with an eavesdropper. Due to the fading of wireless signals and the broadcast nature of wireless channels, transmitted signals over the network may be undecodable at the receiver end or have been eavesdropped by eavesdroppers. Most available buffer-aided relay selection schemes consider either reliability or security issues in wireless communications; rarely is work conducted on both reliability and security issues. This paper proposes a buffer-aided relay selection scheme based on deep Q-learning (DQL) that considers both reliability and security. By conducting Monte Carlo simulations, we then verify the reliability and security performances of the proposed scheme in terms of the connection outage probability (COP) and secrecy outage probability (SOP), respectively. The simulation results show that two-hop wireless relay network can achieve reliable and secure communications by using our proposed scheme. We also performed comparison experiments between our proposed scheme and two benchmark schemes. The comparison results indicate that our proposed scheme outperforms the max-ratio scheme in terms of the SOP.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Deep Q-Learning-Based Buffer-Aided Relay Selection for Reliable and Secure Communications in Two-Hop Wireless Relay Networks

Zhang

Liao

et al. 2023

Sensors

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“…However, in [18], the presence of an eavesdropper in the buffer-aided CRNs is not considered. In [19], a joint relay selection and power allocation scheme in a secure buffer-aided CRN with multiple relays under complex Gaussian fading channels is proposed to maximize the system performance. In the latter work, machine learning is used to optimize the secrecy rate and throughput with delay and secrecy constraints, as an alternative to traditional optimization methods.…”

Section: Related Workmentioning

confidence: 99%

On the secrecy outage analysis of underlay cognitive radio systems with buffer‐aided relaying under Nakagami‐ m channels

2021

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In this work, the physical layer security performance of an underlay cognitive buffer-aided relay network over the general Nakagami-m fading channel model is addressed, where a primary source communicates with a destination via a decode-and-forward relay node in the presence of an eavesdropper and a secondary communication system. The relay is equipped with a finite-size storage equipment or buffer which can store the sequence of received data packets from source and forward it immediately or subsequently in an adequate time-slot. In this way, the buffer relay enables to adopt a link selection scheme in order to detect the best available link, (i.e. the one with higher secrecy rate) among the available data at source or at the relay buffer. The closed-form expression for the secrecy outage probability (SOP), which is a widely adopted performance metric in the considered scenario, is also derived. Numerical results confirm the accuracy of the derived closed-form analytic expression for SOP and indicates the interaction between secrecy performance and the Nakagami channel parameter m. In particular, it is shown that the SOP experiences a significant drop as the Nakagami channel parameter increases for a predefined target secrecy rate.

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“…To boost the sumthroughput and reduce the total energy of Internet-of-Things networks, a rotary-wing unmanned aerial vehicle equipped with an FD access point was introduced [9]. In addition, the authors of [10] utilized a double deep Q-network to solve the throughput maximization and secrecy rate maximization problems in a secure cognitive radio relay network where the relay nodes operated in the FD mode and transmitted jamming signals to the eavesdropper. Furthermore, an optimal power allocation strategy was proposed for the dual-hop FD decodeand-forward relay system to minimize the outage probability.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Omni Surface-Assisted Self-Interference Cancellation for Full-Duplex MISO System

Fang

Chen

Xiao

et al. 2024

IEEE Trans. Wireless Commun.

Self Cite

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The full-duplex (FD) communication can achieve higher spectrum efficiency than conventional half-duplex (HD) communication; however, self-interference (SI) is the key hurdle. This paper is the first work to propose the intelligent omni surface (IOS)-assisted FD multi-input single-output (MISO) FD communication systems to mitigate SI, which solves the frequencyselectivity issue. In particular, two types of IOS are proposed, energy splitting (ES)-IOS and mode switching (MS)-IOS. We aim to maximize data rate and minimize SI power by optimizing the beamforming vectors, amplitudes and phase shifts for the ES-IOS and the mode selection and phase shifts for the MS-IOS. However, the formulated problems are non-convex and challenging to tackle directly. Thus, we design alternative optimization algorithms to solve the problems iteratively. Specifically, the quadratic constraint quadratic programming (QCQP) is employed for the beamforming optimizations, amplitudes and phase shifts optimizations for the ES-IOS and phase shifts optimizations for the MS-IOS. Nevertheless, the binary variables of the MS-IOS render the mode selection optimization intractable, and then we resort to semidefinite relaxation (SDR) and Gaussian randomization procedures to solve it. Simulation results validate the proposed algorithms' efficacy and show the effectiveness of both the IOSs in mitigating SI compared to the case without an IOS.

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Joint Buffer-Aided Hybrid-Duplex Relay Selection and Power Allocation for Secure Cognitive Networks With Double Deep Q-Network

Cited by 23 publications

References 39 publications

Deep Q-Learning-Based Buffer-Aided Relay Selection for Reliable and Secure Communications in Two-Hop Wireless Relay Networks

Deep Q-Learning-Based Buffer-Aided Relay Selection for Reliable and Secure Communications in Two-Hop Wireless Relay Networks

On the secrecy outage analysis of underlay cognitive radio systems with buffer‐aided relaying under Nakagami‐ m channels

Intelligent Omni Surface-Assisted Self-Interference Cancellation for Full-Duplex MISO System

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