Optimization of the parameters in SVM-based spectrum sensing model

DOI

10.2991/itoec-16.2016.62How to use a DOI?

Keywords

Spectrum Sensing, Support Vector Machine, Primary User, Radial Basis Function

Abstract

The process of spectrum sensing plays a key part in Cognitive Radio (CR). In this paper, Support Vector Machine(SVM)is applied to spectrum sensing which can judge whether the Primary User (PU) exists or not for its good performance in many fields. Data set including training set and testing set with different characteristics is generated by laboratory instruments to verify the SVM-based spectrum sensing model of good performance in actual communication environment. To solve the problem of huge training set, the paper focuses on researching the optimal parameters of the number and dimension of training set. The simulation results show that the optimal parameter of Radial Basis Function (RBF) and the size of training set and testing set are different with different characteristics of training set and testing set.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xuping Zhai
AU  - Tian Meng
AU  - Bingbing Yang
PY  - 2016/05
DA  - 2016/05
TI  - Optimization of the parameters in SVM-based spectrum sensing model
BT  - Proceedings of the 2nd Information Technology and Mechatronics Engineering Conference (ITOEC 2016)
PB  - Atlantis Press
SP  - 329
EP  - 332
SN  - 2352-5401
UR  - https://doi.org/10.2991/itoec-16.2016.62
DO  - 10.2991/itoec-16.2016.62
ID  - Zhai2016/05
ER  -