| Fast Automatic Modulation Classification by MDC and kNNC |
|
Cheol-Sun Park, Jong-Won Yang, Sun-Phil Nah, Won Jang |
| MDC와 kNNC를 이용한 고속 자동변조인식 |
|
박철순, 양종원, 나선필, 장원 |
|
국방과학연구소 |
|
|
| Abstract |
|
This paper discusses the fast modulation classifiers capable of classifying both analog and digital modulation signals in wireless communications applications. A total of 7 statistical signal features are extracted and used to classify 9 modulated signals. In this paper, we investigate the performance of the two types of fast modulation classifiers (i.e. 2 nearest neighbor classifiers and 2 minimum distance classifiers) and compare the performance of these classifiers with that of the state of the art for the existing classification methods such as SVM Classifier. Computer simulations indicate good performance on an AWGN channel, even at low signal-to-noise ratios, in case of minimum distance classifiers (MDC for short) and k nearest neighbor classifiers (kNNC for short). Besides a good performance, these type classifiers are considered as ideal candidate to adapt real-time software radio because of their fast modulation classification capability. |
| Key Words:
Modulation Classification, Minimum Distance Classifier, Nearest Neighbor Classifier |
|
PDF Links
Full text via DOI
Download Citation
