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Artificial noise aided secure cognitive beamforming for cooperative MISO-NOMA using SWIPT

Artificial noise aided secure cognitive beamforming for cooperative MISO-NOMA using SWIPT
Artificial noise aided secure cognitive beamforming for cooperative MISO-NOMA using SWIPT
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.
0733-8716
Zhou, Fuhui
24a353b5-2a21-46b1-b04c-b1d8b6acb6f0
Chu, Zheng
2e26321b-20ad-4999-a0d3-7a571c92c0bc
Sun, Haijian
0812962c-df38-4886-94db-5ae37ffe7f04
Hu, Rose Qingyang
5001b455-00dd-49ca-8efb-74a009a5ba9f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhou, Fuhui
24a353b5-2a21-46b1-b04c-b1d8b6acb6f0
Chu, Zheng
2e26321b-20ad-4999-a0d3-7a571c92c0bc
Sun, Haijian
0812962c-df38-4886-94db-5ae37ffe7f04
Hu, Rose Qingyang
5001b455-00dd-49ca-8efb-74a009a5ba9f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Zhou, Fuhui, Chu, Zheng, Sun, Haijian, Hu, Rose Qingyang and Hanzo, Lajos (2018) Artificial noise aided secure cognitive beamforming for cooperative MISO-NOMA using SWIPT. IEEE Journal on Selected Areas in Communications. (doi:10.1109/JSAC.2018.2824622).

Record type: Article

Abstract

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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jsac-accepted - Accepted Manuscript
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More information

Accepted/In Press date: 29 December 2017
e-pub ahead of print date: 9 April 2018

Identifiers

Local EPrints ID: 416985
URI: http://eprints.soton.ac.uk/id/eprint/416985
ISSN: 0733-8716
PURE UUID: aa7917d7-a28a-42f4-93c4-04c07b61072f
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 16 Jan 2018 17:30
Last modified: 07 Oct 2020 05:35

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Contributors

Author: Fuhui Zhou
Author: Zheng Chu
Author: Haijian Sun
Author: Rose Qingyang Hu
Author: Lajos Hanzo ORCID iD

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