Modulation classification for digital modulated signals
Modulation classification of digital modulated signals is gaining importance in modern digital communications. It is known that radio signals travel in space with different frequencies in a very wide band and therefore there are many applications that require signal identification and monitoring. So...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/10356/15942 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Modulation classification of digital modulated signals is gaining importance in modern digital communications. It is known that radio signals travel in space with different frequencies in a very wide band and therefore there are many applications that require signal identification and monitoring. Some of these applications are relating to spectrum management, radio monitoring, wireless communication surveillance, military applications, etc.
The major objective of this FYP project is to classify M-ary QAM signals in presence of Additive White Gaussian Noise (AWGN) into various constellation types and then identify them. The advantages of this method are its simplicity, efficiency, and self-organization, as well as its minimization of the mean square error. The QAM signals are pass through the receiver end are trained to be distinguished into the various constellation points using the K-means Clustering algorithm. The proposed algorithm being flexible can be easily expanded to identify all the M-ary QAM and constellation types. The performance of the algorithm is evaluated. |
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