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Journal Articles Computer Networks Year : 2020

Generalized Nash Equilibrium approach for radio resource sharing and power allocation in vehicular networks

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Abstract

The enabling technology of vehicular networks for Intelligent Transportation Systems (ITS), smart cities and autonomous driving, offers promising on-board services such as road-safety, easy navigation, comfort driving and infotainment. These services can co-exist simultaneously in the system. One challenging issue is to provide the different quality of service (QoS) requirements adequate to each service. This may not be an easy task because of the constrained factors characterizing these networks (e.g., growing number of connected vehicular devices, wireless communications, etc.). In this paper, we investigate the radio resources allocation problem to match different QoS requirements in terms of data rate whilst reducing the interference ratio. We first proposed a radio allocation model that aims to maximize the data rate and minimize the transmission power for all users. However, since not all vehicles use services that require high data rates, it will be more efficient to consider different required data rate for each user. Hence, we develop an efficient model for transmission power allocation that aims to reduce the interference ratio while providing the data rate required by each user. The proposed model is based on Generalized Nash Equilibrium (GNE) game where the users compete to acquire the radio resources. We proposed also two water-filling algorithms to solve the spectrum allocation game during Vehicle-to-Vehicle (V2V) communication over multiple channels. The extensive simulations have shown that our model can satisfy the users regarding different.
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Dates and versions

hal-03260869 , version 1 (30-08-2022)

Licence

Attribution - NonCommercial - CC BY 4.0

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Samira Chouikhi, Lyes Khoukhi, Moez Esseghir, Leila Merghem-Boulahia. Generalized Nash Equilibrium approach for radio resource sharing and power allocation in vehicular networks. Computer Networks, 2020, 182, pp.107490. ⟨10.1016/j.comnet.2020.107490⟩. ⟨hal-03260869⟩
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