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Green-energy-powered cognitive radio networks: Joint time and power allocation
Xu C(许驰); Liang W(梁炜); Yu HB(于海斌)
Department工业控制网络与系统研究室
Source PublicationACM Transactions on Embedded Computing Systems
ISSN1539-9087
2018
Volume17Issue:1Pages:1-18
Indexed BySCI ; EI
EI Accession number20173604117597
WOS IDWOS:000423294100013
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China
KeywordCognitive Radio Networks Resource Allocation Green Energy Energy Harvesting Throughput
AbstractThis 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 SubjectComputer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS KeywordTHROUGHPUT MAXIMIZATION ; RESOURCE-ALLOCATION ; OPTIMIZATION
WOS Research AreaComputer Science
Funding ProjectNational Natural Science Foundation of China[61233007] ; National Natural Science Foundation of China[61533015] ; National Natural Science Foundation of China[71661147005]
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20976
Collection工业控制网络与系统研究室
Corresponding AuthorYu HB(于海斌)
Affiliation1.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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