采用对数预处理的SVM频谱感知方法

doi:10.3969/j.issn.0255-8297.2017.06.006

Abstract

Abstract:

To improve probability of detection and reduce training time, this paper proposes a method of support vector machine (SVM) spectrum sensing based on data preprocessing with a log function. A minimum size of training set is selected, which is applicable with good performance in spectrum sensing. The sample sets are generated with laboratory instruments. The obtained sample sets are pre-processed with a log function to increase the mean difference between sample sets with and without primary users (PU). Experimental results show that, after pre-processing, performance of spectrum sensing is significantly improved under low SNR conditions with detection accuracy 90% or better.

Key words: log function, cognitive radio, spectrum sensing, support vector machine (SVM)

CLC Number:

TP181

ZHAI Xu-ping, MENG Tian, WANG Tao. SVM Spectrum Sensing Based on Data Pre-processing with Log Function[J]. Journal of Applied Sciences, 2017, 35(6): 726-734.

References

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SVM Spectrum Sensing Based on Data Pre-processing with Log Function

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