Spectrum Pricing and Cognitive Radio

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dc.contributor.authorOloyede, Abdulkarim
dc.contributor.authorDavid, G
dc.contributor.authorNasir, Faruk
dc.date.accessioned2021-08-30T17:22:26Z
dc.date.available2021-08-30T17:22:26Z
dc.date.issued2014-05-05
dc.description.abstractWireless service providers (WSP) are facing continuous challenge of enhancing network coverage and capacity to handle ongoing upsurge in data traffic and increased user demand for ubiquitous high quality service. Several economic models have been proposed to provide flexible prices to users and also serve as a control to the network resource. However, the existing pricing schemes available today could still not mitigate the problem of unfairness and congestion. This is expected to be persistent as the demand for data applications keeps increasing. In this paper, we propose a real-time dynamic pricing scheme based on game model that incooperated the current demand, the state of the network and the transmitting power of the users. The model determines the pricing based on the relationship and conflict of interest between the service provider and the user. Results of analysis show that Nash Equilibrium can be achieved when both users and the service providers adopt the use of learning to approximate the utility of each other. The model demonstrates how pricing can be used to simulate the cooperation of users and the service provider to generate a socially, optimal allocation mechanism. Furthermore, we found that if learning is adopted by both the users and the service providers, then, the utility and energy consumed by the users can be improved significantly when compared to a non-learning system.en_US
dc.identifier.citation62en_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/6272
dc.language.isoenen_US
dc.publisherInternational Journal on Wireless Communicationen_US
dc.subjectSpctrun pricingen_US
dc.subjectCognitive Radioen_US
dc.titleSpectrum Pricing and Cognitive Radioen_US

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