A dynamic threshold computing method based on SOM neural network in frequency occupancy analysis
A dynamic threshold computing method based on SOM neural network in frequency occupancy analysis
- Author(s): Miao Yang ; Huiling Dai ; Neng Ye
- DOI: 10.1049/ic.2014.0093
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- Author(s): Miao Yang ; Huiling Dai ; Neng Ye Source: 10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014), 2014 p. 153 – 158
- Conference: 10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)
- DOI: 10.1049/ic.2014.0093
- ISBN: 978-1-84919-845-5
- Location: Beijing, China
- Conference date: 26-28 Sept. 2014
- Format: PDF
Spectrum occupancy measurement and analysis is a very important aspect in frequency resource planning by the reason of frequency shortage for the increasing wireless systems. It is also useful in spectrum sensing in the context of cognitive radio, especially in unlicensed band. Given that, a dynamic decision threshold computing method based on SOM Neural Network in spectrum occupancy analysis is proposed in this paper. This method is designed to cluster sample data into different spaces by network self-learning without knowing the statistics of the measurement data. Simulation with pre-set data is given, and the results show the accuracy and the robustness of the proposed method. This dynamic method is validated with the data derived from the spectrum measurements of 806-960 MHz band in Beijing.
Inspec keywords: radio spectrum management; cognitive radio; pattern clustering; telecommunication computing; self-organising feature maps
Subjects: Neural computing techniques; Communications computing; Radio links and equipment
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