Recognition of communication signal modulation based on SAA-SVM

Author

Huang, Rurong ; Feng, Quanyuan

Author_Institution

Inst. of Microelectron., Southwest Jiaotong Univ., Chengdu, China

Volume

2

fYear

2010

fDate

9-11 July 2010

Firstpage

510

Lastpage

512

Abstract

Support vector machine has a wide range of applications in the communications signal modulation recognition, its parameters directly affect the recognition results, but lack of proper selection methods. In this paper, the simulated annealing algorithm has been utilized for optimization of the parameters C and g of support vector machine classifier. Compared with genetic algorithm, which is a traditional method of performing parameter searching, the rate of recognition of the proposed method increased by 3.58% and optimization time reduced by 27.7%. The results suggest that recognition of communication signal modulation based on SAA-SVM is accurate and feasible.

Keywords

modulation; simulated annealing; support vector machines; telecommunication computing; SAA-SVM; communication signal modulation recognition; optimization; simulated annealing algorithm; support vector machine; Annealing; Modulation; Support vector machines; recognition of communication signal modulation; simulated annealing algorithm; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-5537-9

Type

conf

DOI

10.1109/ICCSIT.2010.5564862

Filename

5564862