Evidence map›Paper›PMID 39619773›Full record

ArticleMobile networks and applications : MONET2023

Joint Node Selection and Power Allocation for Cooperative Positioning Based on Bidding Auction in VANET.

Geng Chen, Lili Cheng, Xiaoxian Kong, Qingtian Zeng, Yu-Dong Zhang

Abstract read
In one paragraph

Article in Mobile networks and applications : MONET, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Geng ChenCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590 China.ORCID 0000-0001-9432-0563
Lili ChengCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590 China.
Xiaoxian KongCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590 China.
Qingtian ZengCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590 China.
Yu-Dong ZhangSchool of Computing and Mathematical Sciences, University of Leicester, Leicester, LE1 7RH UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to buildings blocking GPS and Wi-Fi signals, traditional techniques can't offer the user's required positioning accuracy in resource-constrained underground parking, but the cooperation of agent nodes can provide the exact localization information to improve the positioning accuracy. However, some well-localized agents may not be willing to sacrifice additional power to improve the others' positioning accuracy. To encourage cooperation among nodes and allocate transmission power reasonably, this paper proposes a bidding-auction-based cooperative localization (BACL) algorithm to improve the positioning accuracy of agent nodes by joint node selection incentive and power allocation strategy. Firstly, the contribution of channel parameters and prior localization information of agent nodes for positioning accuracy are quantified and an incentive mechanism of cooperative localization from an economic perspective is proposed. Secondly, a virtual currency incentive rule is developed to compensate agent nodes of cooperative localization reasonably due to the consumption of energy for transmitting their location information. Finally, the simulation results have shown that the proposed BACL algorithm has excellent performance in terms of localization accuracy in resource-constrained scenarios. Compared with the full-power cooperative localization (FPCL) and non-cooperative localization (NCL) algorithms, the proposed BACL algorithm improved the positioning accuracy by 10% and 65%, respectively. Meanwhile, compared with the FPCL algorithm, the proposed algorithm reduced resource consumption by 50%.

Indexed as

Bidding auctionCooperative positioningInternet of vehiclesNode selectionPositioning accuracyPower allocation

Identifiers

PMID39619773
PMCPMC11607065

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.