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In the last decades, the development of the mobile telecommunication industry has triggered the increase of demand for wireless spectrum. Dynamic spectrum management (DSM) concept has been emerged with the development of cognitive radio technologies just to enable efficient utilization of the scarce spectrum. However, DSM will provide significant economic and social benefits only if it becomes widely utilized. For this to occur, the next generation wireless market itself must evolve. This paper analyzes a novel brokering architecture for next generation cognitive radio-based communication platform. We develop a simple competitive economic model among the players of our proposed architecture.

As the usage of cellular phones increases wireless subscribers demand many advanced networking capabilities, especially multimedia applications with very high Quality of Service (QoS) requirements. The limited availability of radio spectrum enforces Mobile Network Operators (MNOs) to have efficient resource management strategies. The goal is to offer services that satisfy the QoS requirements of individual users while achieving an efficient utilization of network resources. This paper considers a resource allocation strategy for cellular networks to be applied during call initiation, handoff and allocation of mobile base stations. Long-term customer retention becomes a major challenge for MNOs due to severe competition in the telecommunications industry. Therefore the MNOs need to understand the customer demographics as well as the customer spending behavior in telecommunications market. Our proposed model combines the information about the customer demographics and usage behavior once the call is initiated. Our hypothesis is that using customer information together with call information yields an efficient customer-oriented resource management strategy. We have performed simulations with different real-life scenarios. Our results show that our proposed model performs better in terms of revenue increase when compared to the First-Come First-Serve based approach.

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