Secrecy Energy Efficiency Maximization for Distributed Intelligent-Reflecting-Surface-Assisted MISO Secure Communications

Song, Huanhuan; Wen, Hong; Tang, Jie; Ho, Pin–Han; Zhao, Runhui

doi:10.1109/jiot.2022.3218664

Cited by 11 publications

(4 citation statements)

References 50 publications

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“…The outage probability is evaluated for the considered IRS system for different fading models under energy harvesting paradigm. The comparison with single IRS-aided system is also performed 47 Secrecy energy efficiency This highlights the use of multiple IRSs to enable secure wireless communication with minimum energy consumption. By optimising the reflection coefficients and active beamforming, the tradeoff between total power consumption and secrecy rate is obtained 48 Sum rate The use of multiple IRSs in UAV system is investigated such that maximum sum rate is achieved with the optimization of UAV altitude and the IRS association.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Energy efficient IRS assisted 6G network for Industry 5.0

Taneja

Rani

Raza

et al. 2023

Sci Rep

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The real world applications are more prone to difficulties of challenges due to fast growth of technologies and inclusion of artificial intelligence (AI) based logical solutions. The massive internet-of-things (IoT) devices are involved in number of Industry 5.0 applications like smart healthcare, smart manufacturing, smart agriculture, smart transportation. Advanced wireless techniques, customization of services and different technologies are experiencing a major transformation. The desire to increase the communication reliability without adding energy overhead is the major challenge for massive IoT enabled networks. To cope up with the above challenges, Industry 5.0 requirements needs to be monitored at the remote level which again adds on the communication challenge. Use of relays in 6G based wireless networks is denied due to high requirement of energy. Therefore in this paper, Intelligent reflecting surfaces (IRSs) assisted energy constrained 6G wireless networks are studied. To provide seamless connection between the communicating mobile nodes, IRS with an array of reflecting elements are configured in the system set up. A use-case scenario of IRS enabled network in Internet-of-Underwater things (IoUT) for smart ocean transportation is also provided. The IRS assisted wireless network is evaluated for target rates achieved. A power consumption model of the IRS supported system is also proposed to optimise the energy efficiency of the system. Further, the paper evaluates the impact of number of reflecting elements N on the IRS and the phase resolution b of each element on the system performance. The energy efficiency improves by 20% for IRS with $$N=100$$ N = 100 with $$b=2$$ b = 2 over IRS with $$b=1$$ b = 1 .

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Energy efficient IRS assisted 6G network for Industry 5.0

Taneja

Rani

Raza

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The secrecy throughput of PU and SU are respectively determined as: η y SU ; y ϵ (JA, NJ ), is a crucial metric for evaluating the secrecy rates achieved in the network. On the other hand, an appropriate metric to combine effectively secrecy and energy is the SEE, which is defined as the ratio of achievable sum secrecy rates to the total power consumed in the network [60]- [61]. Thus SEE is determined as: S y = R PU ,y sec +R SU ,y sec Pp+Ps+wPJ where y ϵ (JA, NJ ) and w ϵ (0, 1), i.e., w = 1 for JA and w = 0 for NJ case.…”

Section: A System Secrecy Throughput (Sst) and Secrecy Energy Efficie...mentioning

confidence: 99%

Physical Layer Secrecy Performance Analysis of Jamming-Assisted Overlay Cognitive NOMA Networks With Hardware Impairments and Multiple Non-Colluding Eavesdroppers

Hema,

Babu

2024

IEEE Access

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This paper investigates the physical layer security (PLS) of non-orthogonal multiple access (NOMA)-enabled overlay cognitive radio networks (NOMA-OCRNs), considering multiple non-colluding eavesdroppers. Here PLS is evaluated in terms of: (i) secrecy outage probability (SOP) of primary user (PU) and secondary user (SU) and (ii) system SOP (SSOP), system secrecy throughput (SST) and secrecy energy efficiency (SEE) of the network. Residual hardware impairments arising from non-ideal hardware and imperfect successive interference cancellation conditions are considered. Firstly, we derive new analytical expressions for the SOPs of PU and SU. Numerical evaluation results show that both PU as well as SU suffer very high SOPs that tend to unity in the high transmit power region. Further, RHI and i-SIC have a significant impact on the secrecy performance. To improve the PLS performance, we propose a jammingassisted framework and develop novel analytical models for determining the SOPs of PU and SU. We derive the asymptotic SOP expressions as well. Detailed analytical and simulation results are presented to demonstrate that the proposed jamming-assisted framework leads to a significant reduction of the SOPs of both PU and SU while exhibiting considerable enhancement of SST and SEE of the network compared to the no-jammer scenario. In the final part of this paper, we utilize a deep learning framework for the precise and fast prediction of the SOPs of PU and SU, that can replace complex mathematical modeling.INDEX TERMS Overlay cognitive radio networks, Non-orthogonal multiple access, Physical layer security, Multiple eavesdroppers, Residual hardware impairments, Performance analysis.

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“…Song et al achieved the maximum secrecy energy efficiency in ref. [25] by hierarchically decoupling optimized parameters of secrecy to the formulation of a feasible convex or analyzable solvable sub-problems. It is achieved with comparatively lower computational complexity.…”

Section: Prior Workmentioning

confidence: 99%

Secure transmission for reconfigurable intelligent surface assisted communication with CV‐DDPG

Gao,

Xu,

Zhang

et al. 2023

IET Communications

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Reconfigurable intelligent surface (RIS) has great potential in securing wireless transmission, and it can flexibly change the wireless communication environment. However, the employment of RIS increases the difficulty in beamforming of base station (BS), and existing schemes cannot be directly utilized to enhance the security of system. Therefore, a reinforcement learning framework to jointly control BS and RIS for the purpose of enhancing the secure performance is proposed. Specifically, the beamforming ia transformed with artificial noise and reflection control as a Markov decision problem (MDP) in complex domain. Then, we develop the deep deterministic policy gradient based on complex‐valued neural networks (CV‐DDPG) to imitate the rules of complex computation. Additionally, the CV‐DDPG is performed as the agent of reinforcement learning to control the BS and RIS, which enables better utilization of the implied phase information of complex values in the system. The simulation results show that the proposed model promotes the performance of the control and greatly improves the secrecy rate of the legitimate user.

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Secrecy Energy Efficiency Maximization for Distributed Intelligent-Reflecting-Surface-Assisted MISO Secure Communications

Cited by 11 publications

References 50 publications

RETRACTED ARTICLE: Energy efficient IRS assisted 6G network for Industry 5.0

RETRACTED ARTICLE: Energy efficient IRS assisted 6G network for Industry 5.0

Physical Layer Secrecy Performance Analysis of Jamming-Assisted Overlay Cognitive NOMA Networks With Hardware Impairments and Multiple Non-Colluding Eavesdroppers

Secure transmission for reconfigurable intelligent surface assisted communication with CV‐DDPG

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