COLLABORATIVE ADAPTATION OF COGNITIVE RADIO PARAMETERS USING ONTOLOGY AND POLICY APPROACH

Cognitive radio is expected to be aware of the changing channel environment and adjust the services and resources accordingly by changing the radio's transmission parameters. In order to achieve automatic adaptation, the radio must have the ability to reason about the facts from the environment or from other radios/nodes, i.e. to infer implicit knowledge from the explicitly represented knowledge. It requires a proper language to represent the knowledge and policies and an inference engine that can process the knowledge and policies. However, such awareness and reasoning capabilities, especially combined with optimization and adaptation, have not been previously reported in the literature. Ontology-Based Radio (OBR) has shown its potential to fulfill the awareness and reasoning requirement of cognitive radio. We aim to refine the OBR concept and apply it to a link optimization use case. The general goal is to maximize the information bit rate per transmitter watt of power. This is attained by fine-tuning the parameters in the transmitter and receiver. In this paper, we show that using the ontology and a policy-based approach, two radio nodes are capable of read/modify their knobs and meters, and thus improve the link performance. In this approach, all the internal and external information of the radio is represented in OWL and the rules to fine-tune each parameter are written in a declarative form and interpreted by a reasoner.