Mapping spectrum consumption models to cognitive radio ontology for automatic inference

Abstract

Radio frequency spectrum management plays a critical role in various domains, including government, military, industrial and personal communications. Current methodology of spectrum management relies primarily on licensing, i.e., giving control over a specific part of the spectrum to a limited number of providers. This approach, however, may lead to an underutilization of the spectrum. To address this problem, various dynamic spectrum access and management approaches have been investigated and some are being actively tested in the field. In the work described in this paper we use the Model-Based Spectrum Management (MBSM) approach to policy-based dynamic spectrum management in which spectrum access policies are represented using Spectrum Consumption Models (SCMs). While in MBSM SCMs are expressed in an XML markup language called SCMML, we add a “logical” layer to MBSM by mapping SCMML to an ontology expressed in Web Ontology Language (OWL)—the formal language used in the Semantic Web. We show that it is possible to use such representations for automatically interpreting policies expressed in this layer by an ontology-based inference engine to derive decisions on the permissions of specific spectrum access requests. The main benefit of using the ontology-based representation is that it does not require addition of any new procedural code and thus new policies can be loaded and used by the system on the fly. The paper focuses on how to implement such a system. Towards this end, it presents two spectrum management related use cases and shows how these use cases are implemented using ontologies. The paper also discusses the advantages of the use of an ontology-based approach to dynamic spectrum management and its potential. Quantitative evaluation of the approach is part of our current work.