Robust AN-Aided Beamforming Design for Secure MISO Cognitive Radio Based on a Practical Nonlinear EH Model

Huang, Yangchao; Li, Zan; Zhou, Fuhui; Zhu, Rui

doi:10.1109/access.2017.2730220

Cited by 24 publications

(22 citation statements)

References 35 publications

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“…These investigations were extended to MIMO systems in [7]- [9]. More recently, the authors in [10] and [11] have proposed optimal resource allocation schemes in CRNs with SWIPT under the non-linear EH model. However, the beamforming design problems in [6]- [11] were formulated in a single objective framework.…”

Section: Introduction a Motivation And Related Workmentioning

confidence: 99%

Robust Resource Allocation for MISO Cognitive Radio Networks Under Two Practical Non-Linear Energy Harvesting Models

et al. 2018

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To achieve a good tradeoff between the consumed power and the harvested power, a robust resource optimization problem is studied in a multiple-input single-output cognitive radio network with simultaneous wireless information and power transfer under imperfect channel state information. Unlike most of the existing works that assume an ideal linear energy harvesting (EH) model, we assume two practical non-linear EH models. In order to solve the resulting challenging non-convex problem, we propose an algorithm based on successive convex approximation and prove that a rank-one solution is obtained in each iteration of the proposed algorithm. Our simulation results quantify the effect of the sensitivity threshold of the EH circuit on the harvested power.

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Section: Introduction a Motivation And Related Workmentioning

confidence: 99%

Robust Resource Allocation for MISO Cognitive Radio Networks Under Two Practical Non-Linear Energy Harvesting Models

et al. 2018

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“…In this paper, a practical non-linear EH model is adopted. According to [41]- [43], the harvesting power of EHRs, denoted by Φ E,A , can be formulated as:…”

Section: Non-linear Energy Harvesting Modelmentioning

confidence: 99%

“…Furthermore, Γ e,A = Γ e,m,k when the EHRs are in the primary network and Γ e,A = Λ s,l,1 − σ 2 e,l when the EHRs are in the secondary network. Note that the noise power is ignored, since it is small compared to the RF signal power [41]- [43].…”

Section: Non-linear Energy Harvesting Modelmentioning

confidence: 99%

Artificial Noise Aided Secure Cognitive Beamforming for Cooperative MISO-NOMA Using SWIPT

Zhou

Chu

Sun

et al. 2018

IEEE J. Select. Areas Commun.

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Cognitive radio (CR) and non-orthogonal multiple access (NOMA) have been deemed two promising technologies due to their potential to achieve high spectral efficiency and massive connectivity. This paper studies a multiple-input singleoutput NOMA CR network relying on simultaneous wireless information and power transfer (SWIPT) conceived for supporting a massive population of power limited battery-driven devices. In contrast to most of the existing works, which use an ideally linear energy harvesting model, this study applies a more practical non-linear energy harvesting model. In order to improve the security of the primary network, an artificial-noise-aided cooperative jamming scheme is proposed. The artificial-noiseaided beamforming design problems are investigated subject to the practical secrecy rate and energy harvesting constraints. Specifically, the transmission power minimization problems are formulated under both perfect channel state information (CSI) and the bounded CSI error model. The problems formulated are non-convex, hence they are challenging to solve. A pair of algorithms either using semidefinite relaxation (SDR) or a cost function are proposed for solving these problems. Our simulation results show that the proposed cooperative jamming scheme succeeds in establishing secure communications and NOMA is capable of outperforming the conventional orthogonal multiple access in terms of its power efficiency. Finally, we demonstrate that the cost function algorithm outperforms the SDR-based algorithm.

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Section: Related Workmentioning

confidence: 99%

“…Thus, by fitting practical measurement data, a logistic function-based (LG) nonlinear EH model was proposed in [23]. As the LG nonlinear EH model is much closer to practical systems, it attracts increasing attention and has been studied in various wireless networks, see e.g., point-to-point networks [26,27], MISO networks [28,29], MIMO networks [30,31], NOMA networks [32], cognitive radio networks [33], and relay networks [34], where most of them adopted the LG nonlinear EH model to optimally allocate the system resources or design the SWIPT receiver's parameters.Since the LG nonlinear EH model is too complex to track, especially for the system outage performance analysis, a piecewise (PW) nonlinear EH model was presented to approximate the LG one in [35], with which the system outage performance was investigated for wireless-powered dual-hop relaying MIMO network in independent Rayleigh fading. Due to its traceability, in [36], it was adopted to analyze and minimize the system outage probability of AF relaying SWIPT networks over Gaussian channels.…”

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confidence: 99%

Outage and Throughput of WPCN-SWIPT Networks with Nonlinear EH Model in Nakagami-m Fading

et al. 2019

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This paper analyzes outage probability and reliable throughput performance of a multi-user wireless-powered communication network-simultaneous wireless information and power transfer (WPCN-SWIPT) network with the logistic function-based (LG) nonlinear energy-harvesting (EH) model in Nakagami-m fading. Power-splitting (PS) receiver architecture is considered. The closed-form expressions of the system outage probability and the system reliable throughput are derived, and then the corresponding asymptotic expressions are also provided to achieve simpler calculation in the high-transmit power scenarios. Simulation results demonstrate the correctness of our derived analytical results and show that the systems under the LG nonlinear and linear EH models have very different performance behaviors. Moreover, since the LG nonlinear EH model is closer to the features of practical EH circuit than the linear one, using the LG nonlinear EH model can avoid the false output results of the system performance evaluation.

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Robust AN-Aided Beamforming Design for Secure MISO Cognitive Radio Based on a Practical Nonlinear EH Model

Cited by 24 publications

References 35 publications

Robust Resource Allocation for MISO Cognitive Radio Networks Under Two Practical Non-Linear Energy Harvesting Models

Robust Resource Allocation for MISO Cognitive Radio Networks Under Two Practical Non-Linear Energy Harvesting Models

Artificial Noise Aided Secure Cognitive Beamforming for Cooperative MISO-NOMA Using SWIPT

Outage and Throughput of WPCN-SWIPT Networks with Nonlinear EH Model in Nakagami-m Fading

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