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End-to-End Throughput Maximization for Underlay Multi-Hop Cognitive Radio Networks with RF Energy Harvesting
Xu C(许驰); Zheng M(郑萌); Liang W(梁炜); Yu HB(于海斌); Liang YC(梁应敞)
Department工业控制网络与系统研究室
Source PublicationIEEE Transactions on Wireless Communications
ISSN1536-1276
2017
Volume16Issue:6Pages:3561-3572
Indexed BySCI ; EI
EI Accession number20172503803828
WOS IDWOS:000403495400003
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China [61233007, 61673371, 71661147005, 61571100, 61631005] ; Youth Innovation Promotion Association, CAS [2015157]
KeywordMulti-hop Underlay Cognitive Radio Networks Energy Harvesting End-to-end Throughput Convex Optimization
AbstractThis paper studies a green paradigm for the underlay coexistence of primary users (PUs) and secondary users (SUs) in energy harvesting cognitive radio networks (EH-CRNs), wherein battery-free SUs capture both the spectrum and the energy of PUs to enhance spectrum efficiency and green energy utilization. To lower the transmit powers of SUs, we employ multi-hop transmission with time division multiple access, by which SUs first harvest energy from the RF signals of PUs, and then, transmit data in the allocated time concurrently with PUs, all in the licensed spectrum. In this way, the available transmit energy of each SU mainly depends on the harvested energy before the turn to transmit, namely energy causality. Meanwhile, the transmit powers of SUs must be strictly controlled to protect PUs from harmful interference. Thus, subject to the energy causality constraint and the interference power constraint, we study the end-to-end throughput maximization problem for optimal time and power allocation. To solve this nonconvex problem, we first equivalently transform it into a convex optimization problem and then propose the joint optimal time and power allocation (JOTPA) algorithm that iteratively solves a series of feasibility problems until convergence. Extensive simulations evaluate the performance of EH-CRNs with JOTPA in three typical deployment scenarios and validate the superiority of JOTPA by making comparisons with two other resource allocation algorithms.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectEngineering, Electrical & Electronic ; Telecommunications
WOS KeywordPOWER TRANSFER ; WIRELESS INFORMATION ; RESOURCE-ALLOCATION ; OPTIMIZATION ; SYSTEMS
WOS Research AreaEngineering ; Telecommunications
Citation statistics
Cited Times:46[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20747
Collection工业控制网络与系统研究室
Corresponding AuthorLiang W(梁炜); Yu HB(于海斌)
Affiliation1.State Key Laboratory of Robotics, 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
3.School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, 2006, Australia
4.University of Electronic Science and Technology of China, Chengdu, 611731, China
Recommended Citation
GB/T 7714
Xu C,Zheng M,Liang W,et al. End-to-End Throughput Maximization for Underlay Multi-Hop Cognitive Radio Networks with RF Energy Harvesting[J]. IEEE Transactions on Wireless Communications,2017,16(6):3561-3572.
APA Xu C,Zheng M,Liang W,Yu HB,&Liang YC.(2017).End-to-End Throughput Maximization for Underlay Multi-Hop Cognitive Radio Networks with RF Energy Harvesting.IEEE Transactions on Wireless Communications,16(6),3561-3572.
MLA Xu C,et al."End-to-End Throughput Maximization for Underlay Multi-Hop Cognitive Radio Networks with RF Energy Harvesting".IEEE Transactions on Wireless Communications 16.6(2017):3561-3572.
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