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Incentive Mechanism for Cooperative Localization in Wireless Networks
- Source :
- IEEE Transactions on Vehicular Technology. 69:15920-15932
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Cooperative localization has emerged as an appealing technology since it can improve the localization performance without any infrastructure change compared with non-cooperative localization. However, some well-localized agents may not be willing to sacrifice additional power to improve the others’ localization accuracy. This paper proposes an incentive mechanism from an economic perspective for cooperative localization, whereby a pricing scheme is designed to lead each agent to the optimal state. A game-theoretic algorithm is proposed where each player (agent) can obtain the optimal budget strategy to minimize its individual utility. To make profits in the game, the relationship between the agent's network condition and its budget strategy is derived. Furthermore, a fairness-aware price allocation rule (PAR) is developed to distribute the budget among the reference agents proportional to each node's contribution. Analytical and numerical results show that agents with better network conditions are more likely to join the cooperation under the proposed incentive mechanism, leading to an improved localization performance.
- Subjects :
- Scheme (programming language)
Mathematical optimization
Computer Networks and Communications
Wireless network
Computer science
Mechanism (biology)
Node (networking)
Aerospace Engineering
020302 automobile design & engineering
02 engineering and technology
Profit (economics)
Incentive
0203 mechanical engineering
Automotive Engineering
Resource management
State (computer science)
Electrical and Electronic Engineering
computer
computer.programming_language
Subjects
Details
- ISSN :
- 19399359 and 00189545
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Vehicular Technology
- Accession number :
- edsair.doi...........3d835f2671bb474af1616f4b658657a1
- Full Text :
- https://doi.org/10.1109/tvt.2020.3037743