Share This Article:

Modulation Index Estimation of Frequency and Phase Modulated Signals

Abstract PP. 773-778
DOI: 10.4236/ijcns.2010.39103    5,805 Downloads   11,572 Views  

ABSTRACT

Modulation index estimation is important in the demodulation and recognition of Angle Modulation (AM) signals which include Frequency Modulation (FM) and Phase Modulation (PM) signals. In this paper, we firstly analyzed the AM signals with baseband modulation types, such as monotone, PSK, FSK, in the time and frequency domain. Then, we established a unified mathematical representation for the AM signals. Finally, we derived a blind estimation algorithm for the modulation index without using any prior knowledge. Simulation results verify the capabilities of the proposed algorithm.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

G. Peng, D. Cai, Z. He and Z. Huang, "Modulation Index Estimation of Frequency and Phase Modulated Signals," International Journal of Communications, Network and System Sciences, Vol. 3 No. 9, 2010, pp. 773-778. doi: 10.4236/ijcns.2010.39103.

References

[1] R. W.Jeremy and D. B. Gary, “A Method for Differentiating between Frequency and Phase Modulated Signals,” Proceedings of 1999 Information, Decision and Control Conference, Adelaide, February 1999, pp. 489-494.
[2] T. Shintaro and M. Eiichiro, “Automatic Classification of Analogue Modulation Signals by Statistical Parameters,” Proceedings of 1999 Military Communications Conference, New Jersey, November 1999, pp. 202-207.
[3] X.-W. Zhong, H. Chen and K.-C. Yi, “Automatic Modulation Recognition of TTC Signals of Satellite,” Chinese Space Science and Technology, Vol. 23, No. 3, 2003, pp. 57-64.
[4] J. He and Q. Guo, “Automatic Recognition of Modulation Scheme in Satellite TT&C Channel,” Proceedings of the 7th International Conference on Electronic Measurement & Instrument, Beijing, August 2005.
[5] A. Engin, “Performance Comparison of Wavelet Families for Analog Modulation Classification Using Expert Discrete Wavelet Neural Network System,” Expert Systems with Applications, Vol. 33, No. 4, 2007, pp. 23-25.
[6] A. Engin and A. Derya, “Using Combination of Support Vector Machines for Automatic Analog Modulation Recognition,” Expert Systems with Applications, Vol. 36, No.1, 2009, pp. 3956-3964.
[7] A. E. EI-Mahdy, “Automatic Modulation Classification of Composite FM/PM Speech Signals in Sensor Arrays over Flat Fading Channel,” IET Communications, Vol. 1, No. 2, 2007, pp. 157-164.
[8] X.-D. Zhangx and Z. Bao, “Communication Signal Processing,” Publishing House of National Defense Industry, Beijing, 2000.
[9] Z.-T. Huang, Y.-Y. Zhou and W.-L. Jiang, “The Automatic Analysis of Intra-pulse Modulation Characteristics Based on the Relatively Non-ambiguity Phase Restoral,” Journals on Communications, Vol. 24, No. 4, 2003, pp.153-160.
[10] Y.-X. Wu, L.-D. Ge and Z.-Y. Xu, “A Novel Identification Method for Commonly Used Digital Modulations,” Acta Electronica Sinica, Vol. 35, No. 4, 2007, pp. 782-785.
[11] Y.-F. Zhanx, Z.-G. Caox and Z.-X. Ma, “Modulation Classification of M-QAM Signals,” Journals on Communications, Vol. 25, No. 2, 2004, pp. 68-74.

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.