Data-Centric Prioritization in a Cognitive Radio Network: A Quality-of-Service Based Design and Integration

The under-/un-utilized radio spectrum is an area of emphasis and potential in an effort to increase utilization. This paper introduces a new matrix into the frequency evaluation/determination methodology. It will reduce the number of decision and network collisions in a cognitive radio network environment. This is achieved via a new paradigm, data centric prioritization (DCP), the exploitation of the unique relationship between the transmitted application data type and a "true best fit" cognitive radio frequency decision in a cognitive radio community cluster. Since application data types during normal wireless device operations vary from user to user and utility to utility, so will the network performance requirements. The network must be able to seamlessly support this diversity and a cognitive radio device is best suited for this task. The concept of associating application-specific design requirements with the network dynamics of the frequency spectrum lends itself to a quality-of-service (QoS) methodology. This paper delves into the usage of a QoS methodology within the cognitive radio cognition cycle.