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  • Mei, XiaojunShanghai Maritime Univ, China;Univ Lisbon, Portugal (author)

RSS-Based Byzantine Fault-Tolerant Localization Algorithm Under NLOS Environment

  • Article/chapterEnglish2021

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  • IEEE,2021
  • printrdacarrier

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  • LIBRIS-ID:oai:DiVA.org:lnu-101622
  • https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-101622URI
  • https://doi.org/10.1109/LCOMM.2020.3027904DOI

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  • Language:English
  • Summary in:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

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  • Localization is one of the most critical tasks in wireless sensor networks, but achieving a relatively accurate location estimation is challenging when there have Byzantine fault and non-line-of-sight (NLOS) bias simultaneously. In this context, a localization method, based on received signal strength (RSS), is proposed in this letter to mitigate the impact of Byzantine fault and NLOS bias on the localization accuracy of wireless sensor networks. The proposed method relies on a Byzantine fault-tolerant localization algorithm (BFLA), which converts the localization problem into a generalized trust-region subproblem (GTRS) by applying certain approximations. In order to obtain a feasible solution to the GTRS, a block-coordinate update (BCU) function with a regularization term is used to divide the localization problem into two subproblems. An iterative method, whose start-point is obtained by an unconstrained squared-range (USR) algorithm, is then used to obtain a solution. Numerical simulations are carried out to show the effectiveness of the proposed method, compared with the state-of-the-art approaches in different scenarios.

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Added entries (persons, corporate bodies, meetings, titles ...)

  • Wu, HuafengShanghai Maritime Univ, China (author)
  • Xian, JiangfengShanghai Maritime Univ, China;Politecn Torino, Italy (author)
  • Chen, BowenLinnéuniversitetet,Institutionen för informatik (IK),Shanghai Maritime Univ, China(Swepub:lnu)bc222cu (author)
  • Shanghai Maritime Univ, China;Univ Lisbon, PortugalShanghai Maritime Univ, China (creator_code:org_t)

Related titles

  • In:IEEE Communications Letters: IEEE25:2, s. 474-4781089-77981558-2558

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By the author/editor
Mei, Xiaojun
Wu, Huafeng
Xian, Jiangfeng
Chen, Bowen
About the subject
NATURAL SCIENCES
NATURAL SCIENCES
and Computer and Inf ...
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IEEE Communicati ...
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Linnaeus University

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