File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: An Efficient Iterative Least Square Method for Indoor Visible Light Positioning Under Shot Noise

TitleAn Efficient Iterative Least Square Method for Indoor Visible Light Positioning Under Shot Noise
Authors
KeywordsCRLB
gradient descent
least square
Visible light positioning
Issue Date1-Feb-2023
PublisherInstitute of Electrical and Electronics Engineers
Citation
IEEE Photonics Journal, 2023, v. 15, n. 1 How to Cite?
AbstractIn this paper, we develop a set of effective algorithms for performing efficient and accurate visible light positioning (VLP) in the presence of shot noise, which is an important component in the received optical signal yet has been largely neglected in prior works. In particular, we formulate the positioning problem as a maximum log-likelihood optimization problem, which is nonconvex so that the standard numerical algorithm such as gradient descent (GD) and stochastic gradient descent (SGD) may not be able to find the global solution. To address this, we propose a novel least-square (LS) solver that can find a sub-optimal solution to the aforementioned non-convex optimization problem. Based on the LS solver, a set of more effective algorithms can be developed to further enhance the optimality of the solution. Specifically, we consider (1) combining the LS solver with GD, giving rise to the GD-LS algorithm; and (2) applying the LS solver in an iterative manner, giving rise to the iterative LS algorithm, which is a novel and efficient positioning algorithm. Moreover, we also provide a closed-form lower bound on the positioning error based on the Cramer-Rao lower bounds (CRLB). Numerical simulation shows that the proposed GD-LS and iterative LS algorithms cannot only achieve high positioning accuracy, but also enjoy low computation complexity: the average positioning accuracy of LS-GD is 0.009 m using computation time 0.046 s, and the iterative LS algorithm can achieve average positioning accuracy 0.023 m with 1.94 x 10(-4)s computation time, which outperform GD and SGD method.
Persistent Identifierhttp://hdl.handle.net/10722/340296
ISSN
2023 Impact Factor: 2.1
2023 SCImago Journal Rankings: 0.558
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, XA-
dc.contributor.authorZou, DF-
dc.contributor.authorHuang, N-
dc.contributor.authorWang, Y-
dc.date.accessioned2024-03-11T10:43:05Z-
dc.date.available2024-03-11T10:43:05Z-
dc.date.issued2023-02-01-
dc.identifier.citationIEEE Photonics Journal, 2023, v. 15, n. 1-
dc.identifier.issn1943-0655-
dc.identifier.urihttp://hdl.handle.net/10722/340296-
dc.description.abstractIn this paper, we develop a set of effective algorithms for performing efficient and accurate visible light positioning (VLP) in the presence of shot noise, which is an important component in the received optical signal yet has been largely neglected in prior works. In particular, we formulate the positioning problem as a maximum log-likelihood optimization problem, which is nonconvex so that the standard numerical algorithm such as gradient descent (GD) and stochastic gradient descent (SGD) may not be able to find the global solution. To address this, we propose a novel least-square (LS) solver that can find a sub-optimal solution to the aforementioned non-convex optimization problem. Based on the LS solver, a set of more effective algorithms can be developed to further enhance the optimality of the solution. Specifically, we consider (1) combining the LS solver with GD, giving rise to the GD-LS algorithm; and (2) applying the LS solver in an iterative manner, giving rise to the iterative LS algorithm, which is a novel and efficient positioning algorithm. Moreover, we also provide a closed-form lower bound on the positioning error based on the Cramer-Rao lower bounds (CRLB). Numerical simulation shows that the proposed GD-LS and iterative LS algorithms cannot only achieve high positioning accuracy, but also enjoy low computation complexity: the average positioning accuracy of LS-GD is 0.009 m using computation time 0.046 s, and the iterative LS algorithm can achieve average positioning accuracy 0.023 m with 1.94 x 10(-4)s computation time, which outperform GD and SGD method.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.relation.ispartofIEEE Photonics Journal-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectCRLB-
dc.subjectgradient descent-
dc.subjectleast square-
dc.subjectVisible light positioning-
dc.titleAn Efficient Iterative Least Square Method for Indoor Visible Light Positioning Under Shot Noise-
dc.typeArticle-
dc.description.naturepreprint-
dc.identifier.doi10.1109/JPHOT.2022.3229052-
dc.identifier.scopuseid_2-s2.0-85144759671-
dc.identifier.volume15-
dc.identifier.issue1-
dc.identifier.isiWOS:000935739800001-
dc.publisher.placePISCATAWAY-
dc.identifier.issnl1943-0647-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats