Fayez, Almohanad Samir2013-06-082013-06-082013-06-07vt_gsexam:819http://hdl.handle.net/10919/23180Software Defined Radios (SDRs) lend themselves to flexibility and extensibility because they<br />depend on software to implement radio functionality. Cognitive Engines (CEs) introduce<br />intelligence to radio by monitoring radio performance through a set of meters and configuring<br />the underlying radio design by modifying its knobs. In Cognitive Radio (CR) applications,<br />CEs intelligently monitor radio performance and reconfigure them to meet it application<br />and RF channel needs. While the issue of introducing computational knobs and meters<br />is mentioned in literature, there has been little work on the practical issues involved in<br />introducing such computational radio controls.<br /><br />This dissertation decomposes the radio definition to reactive models for the CE domain<br />and real-time, or dataflow models, for the SDR domain. By allowing such design space<br />decomposition, CEs are able to define implementation independent radio graphs and rely on<br />a model transformation layer to transform reactive radio models to real-time radio models<br />for implementation. The definition of knobs and meters in the CE domain is based on<br />properties of the dataflow models used in implementing SDRs. A framework for developing<br />this work is presented, and proof of concept radio applications are discussed to demonstrate<br />how CEs can gain insight into computational aspects of their radio implementation during<br />their reconfiguration decision process.<br />ETDIn CopyrightSoftware radioCognitive radio networksModels of ComputationCSPSDFGNU RadioOCCAMDissertation