Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems
The combination of cognitive radio and non-orthogonal multiple access (NOMA) has tremendous potential to achieve high spectral efficiency in the IoT era. In this paper, we focus on the energy-efficient resource allocation of a cognitive multiple-input single-output NOMA system with the aid of simult...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8610078/ |
| _version_ | 1818427921711235072 |
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| author | Sun Mao Supeng Leng Jie Hu Kun Yang |
| author_facet | Sun Mao Supeng Leng Jie Hu Kun Yang |
| author_sort | Sun Mao |
| collection | DOAJ |
| description | The combination of cognitive radio and non-orthogonal multiple access (NOMA) has tremendous potential to achieve high spectral efficiency in the IoT era. In this paper, we focus on the energy-efficient resource allocation of a cognitive multiple-input single-output NOMA system with the aid of simultaneous wireless information and power transfer. Specifically, a non-linear energy harvesting (EH) model is adopted to characterize the non-linear energy conversion property. In order to achieve the green design goal, we aim for the minimization of the system power consumption by jointly designing the transmit beamformer and the receive power splitter subject to the information transmission and EH harvesting requirements of second users (SUs), and the maximum tolerable interference constraints at primary users. However, the formulated optimization problem is non-convex and hard to tackle. By exploiting the classic semi-definite relaxation and successive convex approximation, we propose a penalty function-based algorithm to solve the non-convex problem. The convergence of the proposed algorithm is further proved. Finally, simulation results demonstrate that the non-linear EH model is able to strongly reflect the property of practical energy harvester and the performance gain of the proposed algorithm than the baseline scheme. |
| first_indexed | 2024-12-14T14:53:25Z |
| format | Article |
| id | doaj.art-7d8cc6d890af4ddd89082e6054361e2b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T14:53:25Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7d8cc6d890af4ddd89082e6054361e2b2022-12-21T22:57:04ZengIEEEIEEE Access2169-35362019-01-017172471725510.1109/ACCESS.2019.28923218610078Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT SystemsSun Mao0https://orcid.org/0000-0002-9911-8484Supeng Leng1https://orcid.org/0000-0003-0049-5982Jie Hu2https://orcid.org/0000-0002-5157-0172Kun Yang3School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaThe combination of cognitive radio and non-orthogonal multiple access (NOMA) has tremendous potential to achieve high spectral efficiency in the IoT era. In this paper, we focus on the energy-efficient resource allocation of a cognitive multiple-input single-output NOMA system with the aid of simultaneous wireless information and power transfer. Specifically, a non-linear energy harvesting (EH) model is adopted to characterize the non-linear energy conversion property. In order to achieve the green design goal, we aim for the minimization of the system power consumption by jointly designing the transmit beamformer and the receive power splitter subject to the information transmission and EH harvesting requirements of second users (SUs), and the maximum tolerable interference constraints at primary users. However, the formulated optimization problem is non-convex and hard to tackle. By exploiting the classic semi-definite relaxation and successive convex approximation, we propose a penalty function-based algorithm to solve the non-convex problem. The convergence of the proposed algorithm is further proved. Finally, simulation results demonstrate that the non-linear EH model is able to strongly reflect the property of practical energy harvester and the performance gain of the proposed algorithm than the baseline scheme.https://ieeexplore.ieee.org/document/8610078/Non-orthogonal multiple accesscognitive radio networknon-linear energy harvester |
| spellingShingle | Sun Mao Supeng Leng Jie Hu Kun Yang Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems IEEE Access Non-orthogonal multiple access cognitive radio network non-linear energy harvester |
| title | Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems |
| title_full | Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems |
| title_fullStr | Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems |
| title_full_unstemmed | Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems |
| title_short | Power Minimization Resource Allocation for Underlay MISO-NOMA SWIPT Systems |
| title_sort | power minimization resource allocation for underlay miso noma swipt systems |
| topic | Non-orthogonal multiple access cognitive radio network non-linear energy harvester |
| url | https://ieeexplore.ieee.org/document/8610078/ |
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