Citation
Fong, Kok Leong and Tan, Chee Keong (2017) A Reliable Time-Domain Spectrum Hole Prediction for Cognitive Radio Networks Using Regularized Multi-Layer Perceptron. Wireless Personal Communications, 96 (1). pp. 647-654. ISSN 1572-834X
Text
10.1007%2Fs11277-017-4193-4.pdf Restricted to Repository staff only Download (624kB) |
Abstract
A novel spectrum prediction technique based on multi-layer perceptron is proposed to effectively identify spectrum holes in time domain for cognitive radio networks (CRNs). This scheme adopts a more comprehensive input space (e.g. traffic parameters of primary network) to reduce the sampling bias resulted from simple binary input space (e.g. status of spectrum holes) which is commonly used in the conventional spectrum hole prediction schemes. Additionally, regularization is proposed to mitigate the impact of the noise introduced by the stochastic CRNs. The simulation results show that a more reliable spectrum hole predictor can be obtained if being trained using our proposed novel input space and regularization mechanism.
Item Type: | Article |
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Uncontrolled Keywords: | Cognitive radio networks |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television |
Divisions: | Faculty of Engineering (FOE) |
Depositing User: | Ms Suzilawati Abu Samah |
Date Deposited: | 05 Aug 2020 07:50 |
Last Modified: | 05 Aug 2020 07:50 |
URII: | http://shdl.mmu.edu.my/id/eprint/7033 |
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