Title :
Recognition of digital modulation signals based on statistical parameters
Author :
Sun, Pan-Feng ; Zheng, Zi-Wei ; Li, Man
Author_Institution :
Coll. of Inf. Sci. & Eng., Ningbo Univ., Ningbo, China
Abstract :
To overcome the weak noise immunity of signals´ transient characteristic parameters in domain of modulation recognition, this paper proposes a new expression of transient characteristic parameters and gives the flowchart of recognition program,determination of the thresholds. Thus, ASK2, ASK4, ASK8, PSK2, PSK4, PSK8, FSK2, FSK4 and FSK8 signals can be classified. When SNR=10dB, the average identification probability of 96% can be achieved. The simulations show that transient characteristic parameters with new expression have strong anti-noise ability, they can be as stable and robust signatures.
Keywords :
amplitude shift keying; flowcharting; frequency shift keying; phase shift keying; probability; signal classification; signal denoising; ASK2 modulation signal classification; ASK4 modulation signal classification; ASK8 modulation signal classification; FSK2 modulation signal classification; FSK8 modulation signal classification; PSK2 modulation signal classification; PSK4 modulation signal classification; PSK8 modulation signal classification; average identification probability; digital modulation signal recognition; flowchart; noise figure 10 dB; robust signature; signal transient characteristic statistical parameter; stable signature; strong antinoise ability; weak noise immunity; Character recognition; Digital modulation; Feature extraction; Frequency shift keying; Signal to noise ratio; characteristic parameter; modulation recognition; noise immunity;
Conference_Titel :
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4577-1700-0
DOI :
10.1109/TMEE.2011.6199721