Cognitive radio
Abstract (Summary)
This dissertation addresses the intersection of personal wireless technology and
computational intelligence. The primary research issue addressed is the organization of radio
domain knowledge into data structures processable in real-time that integrate machine learning
and natural language processing technology into software radio. The thesis defines and develops
the cognitive radio architecture. The features needed in the architecture are derived from
cognitive radio use cases. These include inferring user communications context, shaping accessnetwork
demand, and realizing a protocol for real-time radio spectrum rental. Mathematical
foundations for the knowledge-representation architecture are derived by applying point-set
topology to the requirements of the use cases. This results in the set-theoretic ontology of radio
knowledge defined in the Radio Knowledge Representation Language (RKRL). The
mathematical analysis also demonstrates that isochronous radio software is not Turingcomputable.
Instead, it is constrained to a bounded-recursive subset of the total functions. A
rapid-prototype cognitive radio, CR1, was developed to apply these mathematical foundations in
a simulated environment. CR1 demonstrated the principles of cognitive radio and focused the
research issues. This led to an important contribution of this dissertation, the cognitive radio
architecture. This is an open architecture framework for integrating agent-based control, natural
language processing, and machine learning technology into software-defined radio platforms.
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Bibliographical Information:
Advisor:
School:Kungliga Tekniska högskolan
School Location:Sweden
Source Type:Doctoral Dissertation
Keywords:
ISBN:
Date of Publication:01/01/2000