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However, some well-localized agents may not be willing to sacrifice additional power to improve the others\u2019 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%.<\/jats:p>","DOI":"10.1007\/s11036-023-02165-z","type":"journal-article","created":{"date-parts":[[2023,7,28]],"date-time":"2023-07-28T11:02:45Z","timestamp":1690542165000},"page":"1950-1963","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Joint Node Selection and Power Allocation for Cooperative Positioning Based on Bidding Auction in VANET"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9432-0563","authenticated-orcid":false,"given":"Geng","family":"Chen","sequence":"first","affiliation":[]},{"given":"Lili","family":"Cheng","sequence":"additional","affiliation":[]},{"given":"Xiaoxian","family":"Kong","sequence":"additional","affiliation":[]},{"given":"Qingtian","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Yu-Dong","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,28]]},"reference":[{"key":"2165_CR1","doi-asserted-by":"crossref","unstructured":"Wu Q, Zhao Y, Fan Q (2022) Time-dependent performance modeling for platooning communications at intersection","DOI":"10.1109\/JIOT.2022.3161028"},{"issue":"1","key":"2165_CR2","doi-asserted-by":"publisher","first-page":"102778","DOI":"10.1109\/ACCESS.2022.3206359","volume":"10","author":"C Wu","year":"2022","unstructured":"Wu C, Huang Z, Zou Y (2022) Delay constrained hybrid task offloading of internet of vehicle: A deep reinforcement learning method. 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