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dc.contributor.authorZhao, C.
dc.contributor.authorChen, S.
dc.contributor.authorWu, Changzhi
dc.contributor.authorChen, F.
dc.contributor.authorJi, Y.
dc.date.accessioned2018-12-13T09:10:19Z
dc.date.available2018-12-13T09:10:19Z
dc.date.created2018-12-12T02:46:34Z
dc.date.issued2018
dc.identifier.citationZhao, C. and Chen, S. and Wu, C. and Chen, F. and Ji, Y. 2018. Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network. IEEE Access. 6: pp. 52161-52168.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/71503
dc.identifier.doi10.1109/ACCESS.2018.2869524
dc.description.abstract

© 2013 IEEE. Network utility maximization has been widely adopted to allocate the resource of networks. However, it suffers from slow convergence under distributed computational environment. This paper proposes a fast rate control algorithm to maximize network utility for energy harvesting in a wireless sensor network. Energy harvesting and channel bandwidth limits are considered together to formulate as a utility maximization problem. Then, an accelerated distributed gradient method is proposed to solve the problem for energy harvesting. Numerical experiments show that the accelerated method achieves faster convergence to the optimal sampling rate under energy and channel constraints than traditional gradient descent methods.

dc.publisherIEEE Access
dc.titleAccelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network
dc.typeJournal Article
dcterms.source.volume6
dcterms.source.startPage52161
dcterms.source.endPage52168
dcterms.source.issn2169-3536
dcterms.source.titleIEEE Access
curtin.departmentSchool of Design and the Built Environment
curtin.accessStatusFulltext not available


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