Waveform reconstruction from ontological description

  • Leszek LechowiczEmail author
  • Mieczyslaw M. Kokar


This article presents the details of a novel method for ontology-based waveform reconfigurability that allows radios of different hardware or software architectures, using different software APIs and even non-uniform waveform description schemas, to interoperate. In this method cognitive radios share the same base software defined radio ontology, which allows the radios to understand the concepts in a uniform way, thus enabling transfer of more complex concepts from one node to another. In the process of reconfiguration, nodes can receive specifications of waveforms expressed in Web Ontology Language (OWL) and rules and then automatically configure their processing according to the specification. Such specifications contain both structural descriptions of software components and descriptions of finite state machines necessary to compose the waveform from simpler software modules. The waveform configuration process encompasses, first, generating state machines and building a model of the waveform by generating OWL individuals and relationships between them using the inference engine and the specified rules. The constructed model is then used to instantiate state machines and other software components and to connect them according to the model. The result of the overall process is such that a cognitive radio is able to receive a description of a waveform it did not know before (from another cognitive radio) and construct the waveform from the description. Then both radios can use the waveform for further communication. A proof-of-concept system has been built confirming the feasibility of the proposed method. In the process of this system’s evaluation three different waveforms (BPSK31, QPSK31 and RTTY) have been described in OWL and rules, the descriptions were successfully transferred from one node to another and then used by the receiving node to construct fully functional software modules implementing the waveforms.


Cognitive radio Software defined radio Ontology Waveforms Reconfigurability 


  1. 1.
    Wang, J., Brady, D., Baclawski, K., Kokar, M., Lechowicz, L. (2003). The use of ontologies for the self-awareness of the communication nodes. In Proceedings of the Software Defined Radio Technical Conference (SDR’03).Google Scholar
  2. 2.
    Wang, J., Kokar, M., Baclawski, K., Brady, D. (2004) Achieving self-awareness of SDR nodes through ontology-based reasoning and reflection. In SDR Technical Conference, Proceedings of the Software Defined Radio Technical Conference.Google Scholar
  3. 3.
    Moskal, J. (2011). Interfacing a reasoner with heterogeneous selfcontrolling software. PhD Dissertation, Northeastern University.Google Scholar
  4. 4.
    Lechowicz, L., Kokar, M. (2006). Achieving dynamic interoperability of communication: transfer of ontology and rules between nodes. In Proceedings of the Software Defined Radio Technical Conference (SDR’06).Google Scholar
  5. 5.
    Lechowicz, L. Kokar, M. (2007). Composition, equivalence and interoperability: An example. In Proceedings of the Software Defined Radio Technical Conference (SDR’07).Google Scholar
  6. 6.
    Wireless Innovation Forum. (2010). Description of the cognitive radio ontology. Working Document WINNF-10-S-0007 29 Augt 2010.Google Scholar
  7. 7.
    OWL 2 Web Ontology Language. Document Overview. W3C Recommendation 27 October 2009.
  8. 8.
    Matheus, C. Baclawski, K. Kokar, M. (2006). BaseVISor: A triples-based inference engine outfitted to process Ruleml and r-entailment rule. In Proceedings of the 2nd International Conference on Rules and Rule Languages for the Semantic Web, Athens, GA.Google Scholar
  9. 9.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J. (1995). Design Patterns: Elements of Reusable Object-Oriented Software. Boston, MA: Addison-Wesley.Google Scholar
  10. 10.
    OMG Unified Modeling Language (OMG UML), Superstructure, Version 2.4.1, Object Management Group. (2011)
  11. 11.
    Fldigi (Fast Light Digital Modem Application)
  12. 12.
    SDR Forum. (2008). SDRF Cognitive Radio Definitions. SDRF-06-P-0009-V1.0.0, Sep 10.Google Scholar
  13. 13.
    Gurari, E. M. (1982). The Equivalence Problem for Deterministic Two-Way Sequential Transducers is Decidable. SIAM Journal on Computing, 11(3), 448–452.CrossRefzbMATHMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringNortheastern UniversityBostonUSA

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