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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuqing Huang Jiao Wang Hong Jiang |
| Copyright Year | 2010 |
| Abstract | Cognitive radio (CR) is an intelligent wireless communication system and the core of it is the cognitive engine. Cognitive engine is expected to implement cognitive learning, inference, decision-making through the artificial intelligence technology to decide a specific radio configuration (i.e. carrier frequency, modulation type, power, etc.) according to the changing of environment. In this paper, a cognitive radio learning inference and decision-making engine based on Bayesian network (BN) is proposed to obtain the optimum configuration rules adapt to the variation of the environment with the learning and inference algorithm of Bayesian network. Simulation results show the feasibility and validity of modeling the cognitive learning inference and decision-making engine with Bayesian network. |
| Starting Page | 258 |
| Ending Page | 261 |
| File Size | 355100 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769540115 |
| e-ISBN | 9781424465989 |
| DOI | 10.1109/NSWCTC.2010.195 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | inference Decision making learning Cognitive radio Engines Learning Wireless communication cognitive radio Bayesian methods decision-making Chromium Frequency cognitive engine Artificial intelligence Intelligent systems Bayesian network |
| Content Type | Text |
| Resource Type | Article |
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