Skip to main content

Interference Excision in Spread Spectrum Communications Using Adaptive Positive Time-Frequency Analysis


This paper introduces a novel algorithm to excise single and multicomponent chirp-like interferences in direct sequence spread spectrum (DSSS) communications. The excision algorithm consists of two stages: adaptive signal decomposition stage and directional element detection stage based on the Hough-Radon transform (HRT). Initially, the received spread spectrum signal is decomposed into its time-frequency (TF) functions using an adaptive signal decomposition algorithm, and the resulting TF functions are mapped onto the TF plane. We then use a line detection algorithm based on the HRT that operates on the image of the TF plane and detects energy varying directional elements that satisfy a parametric constraint. Interference is modeled by reconstructing the corresponding TF functions detected by the HRT, and subtracted from the received signal. The proposed technique has two main advantages: (i) it localizes the interferences on the TF plane with no cross-terms, thus facilitating simple filtering techniques based on thresholding of the TF functions, and is an efficient way to excise the interference; (ii) it can be used for the detection of any directional interferences that can be parameterized. Simulation results with synthetic models have shown successful performance with linear and quadratic chirp interferences for single and multicomponent interference cases. The proposed method excises the interference even under very low SNR conditions of dB, and the technique could be easily extended to any interferences that could be represented by a parametric equation in the TF plane.



  1. 1.

    Yang W, Bi G: Adaptive wavelet packet transform-based narrowband interference canceller in DSSS systems. Electronics Letters 1997,33(14):1189-1190. 10.1049/el:19970817

    Article  Google Scholar 

  2. 2.

    Ranheim A: Narrowband interference rejection in direct-sequence spread-spectrum system using time-frequency decomposition. IEE Proceedings: Communications 1995,142(6):393-400. 10.1049/ip-com:19952299

    Article  Google Scholar 

  3. 3.

    Poor HV, Wang X: Adaptive suppression of narrowband digital interferers from spread spectrum signals. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '96), May 1996, Atlanta, Ga, USA 2: 1061-1064.

    Google Scholar 

  4. 4.

    Liu L, Ge H: Time-varying AR modeling and subspace projection for FM jammer suppression in DS/SS-CDMA systems. Proceedings of the 37th Asilomar Conference on Signals, Systems and Computers (ACSSC '03), November 2003, Pacific Grove, Calif, USA 1: 623-627.

    Google Scholar 

  5. 5.

    Rao KD, Swamy MNS, Plotkin EI: A nonlinear adaptive filter for narrowband interference mitigation in spread spectrum systems. Signal Processing 2005,85(3):625-635. 10.1016/j.sigpro.2004.11.005

    Article  MATH  Google Scholar 

  6. 6.

    Laster JD, Reed JH: Interference rejection in digital wireless communications. IEEE Signal Processing Magazine 1997,14(3):37-62. 10.1109/79.587051

    Article  Google Scholar 

  7. 7.

    Cohen L: Time-frequency distributions-a review. Proceedings of the IEEE 1989,77(7):941-981. 10.1109/5.30749

    Article  Google Scholar 

  8. 8.

    Amin MG: Interference mitigation in spread spectrum communication systems using time-frequency distributions. IEEE Transactions on Signal Processing 1997,45(1):90-101. 10.1109/78.552208

    MathSciNet  Article  Google Scholar 

  9. 9.

    Barbarossa S, Scaglione A: Adaptive time-varying cancellation of wideband interferences in spread-spectrum communications based on time-frequency distributions. IEEE Transactions on Signal Processing 1999,47(4):957-965. 10.1109/78.752594

    Article  Google Scholar 

  10. 10.

    Krongold BS, Kramer ML, Ramchandran K, Jones DL: Spread spectrum interference suppression using adaptive time-frequency tilings. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97), April 1997, Munich, Germany 3: 1881-1884.

    Google Scholar 

  11. 11.

    Ouyang X, Amin MG: Short-time Fourier transform receiver for nonstationary interference excision in direct sequence spread spectrum communications. IEEE Transactions on Signal Processing 2001,49(4):851-863. 10.1109/78.912929

    Article  Google Scholar 

  12. 12.

    Bultan A, Akansu AN: A novel time-frequency exciser in spread spectrum communications for chirp-like interference. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '98), May 1998, Seattle, Wash, USA 6: 3265-3268.

    Google Scholar 

  13. 13.

    Suleesathira R, Chaparro LF: Jammer excision in spread spectrum using discrete evolutionary-Hough transform and singular value decomposition. Proceedings of the 10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing (SSAP '00), August 2000, Pennsylvania, Pa, USA 519-523.

    Google Scholar 

  14. 14.

    Tazebay MV, Akansu AN: Adaptive subband transforms in time-frequency excisers for DSSS communications systems. IEEE Transactions on Signal Processing 1995,43(11):2776-2782. 10.1109/78.482125

    Article  Google Scholar 

  15. 15.

    Matz G, Hlawatsch F: Time-frequency projection filters: online implementation, subspace tracking, and application to interference excision. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '02), May 2002, Orlando, Fla, USA 2: 1213-1216.

    Google Scholar 

  16. 16.

    Amin MG, Mandapati GR: Nonstationary interference excision in spread spectrum communications using projection filtering methods. Proceedings of the 32nd Asilomar Conference on Signals, Systems and Computers, November 1998, Pacific Grove, Calif, USA 1: 827-831.

    Google Scholar 

  17. 17.

    Krishnan S: Adaptive signal processing techniques for analysis of knee joint vibroarthrographic signals, Ph.D. thesis. University of Calgary, Alberta, Canada; 1999.

    Google Scholar 

  18. 18.

    Cohen L, Posch T: Positive time-frequency distribution functions. IEEE Transactions on Acoustics, Speech, and Signal Processing 1985,33(1):31-38. 10.1109/TASSP.1985.1164512

    Article  Google Scholar 

  19. 19.

    Loughlin PJ, Pitton JW, Atlas LE: Construction of positive time-frequency distributions. IEEE Transactions on Signal Processing 1994,42(10):2697-2705. 10.1109/78.324735

    Article  Google Scholar 

  20. 20.

    Mallat SG, Zhang Z: Matching pursuits with time-frequency dictionaries. IEEE Transactions on Signal Processing 1993,41(12):3397-3415. 10.1109/78.258082

    Article  MATH  Google Scholar 

  21. 21.

    Erkucuk S, Krishnan S: Time-frequency filtering of interferences in spread spectrum communications. Proceedings of the 7th International Symposium on Signal Processing and Its Applications (ISSPA '03), July 2003, Paris, France 2: 323-326.

    Google Scholar 

  22. 22.

    Rangayyan RM, Krishnan S: Feature identification in the time-frequency plane by using the Hough-Radon transform. Pattern Recognition 2001,34(6):1147-1158. 10.1016/S0031-3203(00)00073-X

    Article  MATH  Google Scholar 

  23. 23.

    Duda RO, Hart PE: Use of the Hough transformation to detect lines and curves in pictures. Communications of the ACM 1972,15(1):11-15. 10.1145/361237.361242

    Article  MATH  Google Scholar 

  24. 24.

    Herman GT: Image Reconstruction from Projections. The Fundamentals of Computerized Tomography. Academic Press, New York, NY, USA; 1980.

    Google Scholar 

  25. 25.

    Xu L, Oja E, Kultanen P: A new curve detection method: randomized Hough transform (RHT). Pattern Recognition Letters 1990,11(5):331-338. 10.1016/0167-8655(90)90042-Z

    Article  MATH  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Sridhar Krishnan.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Krishnan, S., Erküçük, S. Interference Excision in Spread Spectrum Communications Using Adaptive Positive Time-Frequency Analysis. J Wireless Com Network 2007, 014916 (2007).

Download citation


  • Line Detection
  • Detection Stage
  • Directional Interference
  • Direct Sequence Spread Spectrum
  • Spread Spectrum Communication