Abstract
This chapter presents an adaptive networking platform using WiFi/WiMAX technologies for cognitive vehicle-to-roadside communications, which can be used to transfer safety messages and provide Internet access for mobile users inside vehicles. The proposed platform is based on a heterogeneous multihop cluster-based vehicular network, where a vehicular node can choose to play the role of a gateway or a client. The gateway nodes communicate directly with a roadside base station through a WiMAX link. The client nodes connect to the gateways through WiFi links. Traffic from client nodes are relayed by the gateways to a roadside base station. The vehicular nodes are the self-interest (i.e., rational) and have capability to learn and adapt decision to achieve their objectives independently. A decision-making framework is proposed for this WiFi/WiMAX platform. This distributed decision-making framework, which enables the vehicular nodes with cognitive capability, is modeled and analyzed using game theory. Also, a Q-learning algorithm is used in vehicular nodes to provide the cognitive capability to learn and adapt their decision. Dynamics of Q-learning algorithm can be modeled as an evolutionary game.
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This work was supported by the AUTO21 NCE research grant for the project F303-FVT.
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Niyato, D., Hossain, E., Issariyakul, T. (2011). An Adaptive WiFi/WiMAX Networking Platform for Cognitive Vehicular Networks. In: Yu, F. (eds) Cognitive Radio Mobile Ad Hoc Networks. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6172-3_12
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DOI: https://doi.org/10.1007/978-1-4419-6172-3_12
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