| Green-energy-powered cognitive radio networks: Joint time and power allocation | |
Xu C(许驰) ; Liang W(梁炜); Yu HB(于海斌)
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| Department | 工业控制网络与系统研究室 |
| Source Publication | ACM Transactions on Embedded Computing Systems
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| ISSN | 1539-9087 |
| 2018 | |
| Volume | 17Issue:1Pages:1-18 |
| Indexed By | SCI ; EI |
| EI Accession number | 20173604117597 |
| WOS ID | WOS:000423294100013 |
| Contribution Rank | 1 |
| Funding Organization | National Natural Science Foundation of China |
| Keyword | Cognitive Radio Networks Resource Allocation Green Energy Energy Harvesting Throughput |
| Abstract | This article studies a green-energy-powered cognitive radio network (GCRN) in an underlay paradigm, wherein multiple battery-free secondary users (SUs) capture both the spectrum and the energy of primary users (PUs) to communicate with an access point (AP). By time division multiple access, each SU transmits data to AP in the allocated time and harvests energy from the RF signals of PUs otherwise, all in the same licensed spectrum concurrently with PUs. Thus, the transmit power of each SU is jointly constrained by the peak interference power at PU and the harvested energy of SU. With the formulated green coexistence paradigm, we investigate the sum-Throughput maximization problem with respect to time and power allocation, which is non-convex. To obtain the optimal resource allocation, we propose a joint optimal time and power allocation (JOTPA) algorithm that first transforms the original problem into a convex optimization problem with respect to time and energy allocation, and then solve it by iterative Lagrange dual decomposition. To comprehensively evaluate the performance of the GCRN with JOTPA, we deploy the GCRN in three typical scenarios and compare JOTPA with the equal time and optimal power allocation (ETOPA) algorithm. Extensive simulations show that the deployment of the GCRN significantly influences the throughput performance and JOTPA outperforms ETOPA under all considered scenarios. |
| Language | 英语 |
| WOS Subject | Computer Science, Hardware & Architecture ; Computer Science, Software Engineering |
| WOS Keyword | THROUGHPUT MAXIMIZATION ; RESOURCE-ALLOCATION ; OPTIMIZATION |
| WOS Research Area | Computer Science |
| Funding Project | National Natural Science Foundation of China[61233007] ; National Natural Science Foundation of China[61533015] ; National Natural Science Foundation of China[71661147005] |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.sia.cn/handle/173321/20976 |
| Collection | 工业控制网络与系统研究室 |
| Corresponding Author | Yu HB(于海斌) |
| Affiliation | 1.State Key Laboratory of Robotics and Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.University of Chinese Academy of Sciences, Beijing 100049, China |
| Recommended Citation GB/T 7714 | Xu C,Liang W,Yu HB. Green-energy-powered cognitive radio networks: Joint time and power allocation[J]. ACM Transactions on Embedded Computing Systems,2018,17(1):1-18. |
| APA | Xu C,Liang W,&Yu HB.(2018).Green-energy-powered cognitive radio networks: Joint time and power allocation.ACM Transactions on Embedded Computing Systems,17(1),1-18. |
| MLA | Xu C,et al."Green-energy-powered cognitive radio networks: Joint time and power allocation".ACM Transactions on Embedded Computing Systems 17.1(2018):1-18. |
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