Low complexity demodulator for BFSK waveforms based on polygonal approximation

  • Jorge Torres-Gómez Instituto Superior Politécnico José Antonio Echeverría
  • Fidel Hernández-Montero Universidad de Mondragón
  • Joachim Habermann University of Applied Science Technische Hochschule Mittelhessen (THM)
Keywords: BFSK, digital demodulation, polygonal approximation


The  present  article  relates  in  general  to  digital  demodulation  of  Binary  Frequency  Shift  Keying  (BFSK  waveform).  The  objective  of  the  present  research is to obtain a new processing method for demodulating BFSK-signals in order to reduce hardware complexity in comparison with other reported. The solution proposed here makes use of the theories of matched filters and curve segmentation. The article describes the integration and configuration of a Sampler Correlator and polygonal segmentation blocks in order to obtain a digital receiver for properly demodulating the signal received. The proposed solution  is  shown  to  reduce  dramatically  the  complexity  in  hardware  and  has a better performance regarding noise in comparison with other reported. Theoretical  details  concerning  limits  of  applicability  are  also  given  by  closed-form  expressions.  Simulation  experiments  are  illustrated  to  validate  the overall performance.

= 20 veces | PDF
= 10 veces|


Download data is not yet available.

Author Biographies

Jorge Torres-Gómez, Instituto Superior Politécnico José Antonio Echeverría

Departamento de Telecomunicaciones y Telemática

Fidel Hernández-Montero, Universidad de Mondragón

Grupo de investigación Teoría de la Señal y Comunicaciones

Joachim Habermann, University of Applied Science Technische Hochschule Mittelhessen (THM)

Department of Electrical Engineering and Information Technology, professor


M. Lont, D. Milosevic, G. Dolmans, A. Roermund. “Implications of I/Q Imbalance, Phase Noise and Noise Figure for SNR and BER of FSK Receivers”. IEEE Trans. Circuits Syst. Regul. Pap. Vol. 60. 2013. pp. 2187-2198.

K. Peng, C. Lin, C. Chao. “A Novel Three-Point Modulation Technique for Fractional-N Frequency Synthesizer Applications”. Radioengineering. Vol. 22. 2013. pp. 269-275.

I. Veřtát, J. Mráz. “Hybrid M-FSK/DQPSK Modulations for CubeSat Picosatellites”. Radioengineering. Vol. 2. 2013. pp. 389-393.

B. Sklar. Digital Communications, Fundamentals and Applications. 2nd ed. Ed. Prentice Hall. New Jersey, USA. 2001. pp. 124-125.

K. Farrell, P. McLane. “Performance of the crosscorrelator receiver for binary digital frequency modulation”. IEEE Trans. Commun. Vol. 45. 1997. pp. 573-582.

H. Kang, D. Kim, S. Park. Coarse frequency offset estimation using a delayed auto-quadricorrelator in OFDM-based WLANs. Proceedings of the 3rd International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). Budapest, Hungary. 2011. pp. 1-4.

G. Ordu, A. Kruth, S. Sappok, R. Wunderlich, and S. Heinen. A quadricorrelator demodulator for a Bluetooth low-IF receiver. Proceedings of the IEEE Radio Frequency Integrated Circuits (RFIC) Symposium, Digest of Papers. Forth Worth, USA, 2004. pp. 351-354.

R. Yang, S. Chen, S. Liu. “A 3.125-Gb/s clock and data recovery circuit for the 10-Gbase-LX4 Ethernet”. IEEE J. Solid-State Circuits. Vol. 39. 2004. pp. 1356- 1360.

P. Egau. “Correlation systems in radio astronomy and related fields”. IEE Proceedings F, Commun. Radar Signal Process. Vol. 131. 1984. pp. 32-39.

T. Ahn, C. Yoon, Y. Moon. An adaptive frequency calibration technique for fast locking wideband frequency synthesizers. Proceedings of the 48th Midwest Symposium on Circuits and Systems. Vol. 2. Ohio, USA. 2005. pp. 1899-1902.

Y. Lee, T. Cheatham, J. Wiesner. “Application of Correlation Analysis to the Detection of Periodic Signals in Noise”. IRE. Vol. 38. 1958. pp. 1165-1171.

J. Iñesta, M. Buendí, M. Sarti. “Reliable polygonal approximations of imaged real objects through dominant point detection”. Pattern Recognit. Vol. 31. 1998. pp. 685-697.

Y. Zhu, L. Seneviratne. “Optimal polygonal approximation of digitised curves”. IEE Proc. Vis. Image and Signal Process. Vol. 144. 1997. pp. 8-14.

P. Yin. “Ant colony search algorithms for optimal polygonal approximation of plane curves”. Pattern Recognit. Vol. 36. 2003. pp. 1783-1797.

C. Fahn, J. Wang, J. Lee. “An adaptive reduction procedure for the piecewise linear approximation of digitized curves”. IEEE Trans. Pattern Anal. Mach. Intell. Vol. 11. 1989. pp. 967-973.

J. Sklansky, V. Gonzalez. “Fast polygonal approximation of digitized curves”. Pattern Recognit. Vol. 12. 1980. pp. 327-331.

D. Eu, G. Toussaint. “On Approximating Polygonal Curves in Two and Three Dimensions”. Cvgip Graph. Models Image Process. Vol. 56. 1994. pp. 231-246.

K. Ku, P. Chui. “Polygonal approximation of digital curve by graduate iterative merging”. Electron. Lett. Vol. 31. 1995. pp. 444-446.

B. Ray, K. Ray. “Determination of optimal polygon from digital curve using L1 norm”. Pattern Recognit. Vol. 26. 1993. pp. 505-509.

Y. Kurozumi, W. Davis. “Polygonal approximation by the minimax method”. Comput. Graph. Image Process. Vol. 19. 1982. pp. 248-264

K. Wall, P. Danielsson. “A fast sequential method for polygonal approximation of digitized curves”. Comput. Vis. Graph. Image Process. Vol. 28. 1984. pp. 220-227.

C. Williams. “An efficient algorithm for the piecewise linear approximation of planar curves”. Comput. Graph. Image Process. Vol. 8. 1978. pp. 286-293.

A. Oppenheim, R. Schafer. Discrete-time signal processing. 3rd ed. Ed. Prentice Hall. Upper Saddle River, USA. 2010. pp. 550-553.

A. Carlson, P. Crilly, J. Rutledge. Communication Systems: An introduction to Signals and Noise in Electrical Communication. 4th ed. Ed. McGraw-Hill. New York, USA. 2002. pp. 555-556.

How to Cite
Torres-Gómez J., Hernández-Montero F., & Habermann J. (2015). Low complexity demodulator for BFSK waveforms based on polygonal approximation. Revista Facultad De Ingeniería Universidad De Antioquia, (74), 50-59. Retrieved from https://revistas.udea.edu.co/index.php/ingenieria/article/view/19422