Title :
A Survey of Artificial Intelligence for Cognitive Radios
Author :
He, An ; Bae, Kyung Kyoon ; Newman, Timothy R. ; Gaeddert, Joseph ; Kim, Kyouwoong ; Menon, Rekha ; Morales-Tirado, Lizdabel ; Neel, James Jody ; Zhao, Youping ; Reed, Jeffrey H. ; Tranter, William H.
Author_Institution :
Bradley Dept. of Electr. & Comput. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
fDate :
5/1/2010 12:00:00 AM
Abstract :
Cognitive radio (CR) is an enabling technology for numerous new capabilities such as dynamic spectrum access, spectrum markets, and self-organizing networks. To realize this diverse set of applications, CR researchers leverage a variety of artificial intelligence (AI) techniques. To help researchers better understand the practical implications of AI to their CR designs, this paper reviews several CR implementations that used the following AI techniques: artificial neural networks (ANNs), metaheuristic algorithms, hidden Markov models (HMMs), rule-based systems, ontology-based systems (OBSs), and case-based systems (CBSs). Factors that influence the choice of AI techniques, such as responsiveness, complexity, security, robustness, and stability, are discussed. To provide readers with a more concrete understanding, these factors are illustrated in an extended discussion of two CR designs.
Keywords :
case-based reasoning; cognitive radio; hidden Markov models; neural nets; ontologies (artificial intelligence); telecommunication computing; artificial intelligence; artificial neural networks; case-based systems; cognitive radio; dynamic spectrum access; hidden Markov models; metaheuristic algorithms; ontology-based systems; rule-based systems; self-organizing networks; spectrum markets; Artificial intelligence (AI); cognitive engine (CE); cognitive radio (CR);
Journal_Title :
Vehicular Technology, IEEE Transactions on
DOI :
10.1109/TVT.2010.2043968