Mitigating Near-field Interference in Laptop Embedded Wireless Transceivers | Journal of Signal Processing Systems Skip to main content
Springer Nature Link
Log in

Mitigating Near-field Interference in Laptop Embedded Wireless Transceivers

  • Published:
Journal of Signal Processing Systems Aims and scope Submit manuscript

Abstract

In laptop and desktop computers, clocks and busses generate significant radio frequency interference (RFI) for the embedded wireless data transceivers. RFI is well modeled using non-Gaussian impulsive statistics. Data communication transceivers, however, are typically designed under the assumption of additive Gaussian noise and exhibit degradation in communication performance in the presence of RFI. When detecting a signal in additive impulsive noise, Spaulding and Middleton showed a potential improvement in detection of 25 dB at a bit error rate of 10 − 5 when using a Bayesian detector instead of a standard correlation receiver. In this paper, we model RFI using Middleton Class A and Symmetric Alpha Stable (S αS) models. The contributions of this paper are to evaluate (1) the performance vs. complexity of parameter estimation algorithms, (2) the closeness of fit of RFI models to the measured interference data from a computer platform, (3) the communication performance vs. computational complexity tradeoffs in receivers designed to mitigate RFI modeled as Class A interference, (4) the communication performance vs. computational complexity tradeoffs in filtering and detections methods to combat RFI modeled as S αS interference, and (5) the approximations to filtering and detection methods developed to mitigate RFI for a computationally efficient implementation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  1. Nassar, M., Gulati, K., Sujeeth, A. K., Aghasadeghi, N., Evans, B. L., & Tinsley, K. R. (2008). Mitigating near-field interference in laptop embedded wireless transceivers. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing.

  2. Gulati, K., Chopra, A., Heath, R. W., Evans, B. L., Tinsley, K.R., & Lin, X. E. (2008). MIMO receiver design in the presence of radio frequency interference. Proc. IEEE Global Comm. Conf.

  3. Shi, J., Bettner, A., Chinn, G., Slattery, K., & Dong, X. (2006). A study of platform EMI from LCD panels—impact on wireless, root causes and mitigation methods. IEEE International Symposium on Electromagnetic Compatibility, 3, 626–631.

    Google Scholar 

  4. Middleton, D. (1999). Non-Gaussian noise models in signal processing for telecommunications: New methods and results for class A and class B noise models. IEEE Transactions on Information Theory, 45(4), 1129–1149.

    Article  MATH  MathSciNet  Google Scholar 

  5. Gonzalez, J. G., & Arce, G. R. (2001). Optimality of the myriad filter in practical impulsive-noise enviroments. IEEE Transactions on Signal Processing, 49(2), 438–441.

    Article  Google Scholar 

  6. Spaulding, A., & Middleton D. (1977). Optimum reception in an impulsive interference enviroment-part I: Coherent detection. IEEE Transactions on Communications, 25(9), 910–923.

    Article  MATH  Google Scholar 

  7. Ambike, S., Ilow, J., & Hatzinakos, D. (1994). Detection for binary transmission in a mixture of Gaussian noise and impulsive noise modeled as an alpha-stable process. IEEE Signal Processing Letters, 1, 55–57.

    Article  Google Scholar 

  8. Havarasan, P., Haines, M., Skinner, H., & Justice, F. (2000). Current and future EMI challenges at Intel and how to manage them. Proceedings of the IEEE International Symposium on Electromagnetic Compatibility, 1, 281–283.

    Google Scholar 

  9. Morse, E. A. (1995). A method for EMI evaluation of notebook computer liquid crystal display panels while eliminating the contribution of computer generated EMI. Proceedings of the IEEE International Symposium on Electromagnetic Compatibility (pp. 343–346).

  10. Zeeff, T. M., Hubing, T. H., Drewniak, J. L., Dussroff, R. E., & Doren, T. P. V. (2000). EMC analysis of an 18” LCD monitor. Proceedings of the IEEE International Symposium on Electromagnetic Compatibility, 1, 169–173.

    Google Scholar 

  11. Zabin, S. M., & Poor, H. V. (1991). Efficient estimation of class A noise parameters via the EM algorithm. IEEE Transactions on Information Theory, 37(1), 60–72.

    Article  MATH  Google Scholar 

  12. Tsihrintzis, G. A., & Nikias, C. L. (1996). Fast estimation of the parameters of alpha-stable impulsive interference. IEEE Transactions on Signal Processing, 44(6) 1492–1503.

    Article  Google Scholar 

  13. Bilmes, J. (1998). A gentle tutorial of the EM [expectation-maximization] algorithm and its application to parameter estimation for Gaussian mixture and hidden markov models. Int. Computer Science Institute, Tech. rep.

  14. Cover, T. M., & Thomas, J. A. (2006). Elements of information theory. New York: Wiley.

    MATH  Google Scholar 

  15. Miller, J., & Thomas J. (1972). Detectors for discrete-time signals in non-Gaussian noise. IEEE Transactions on Information Theory, 18, 241–250.

    Article  MATH  Google Scholar 

  16. Adlard, J., Tozer, T., & Burr, A. (1999). Interference rejection in impulsive noise for VLF communications. IEEE Proceedings of the Military Communications Conference, 1, 296–300.

    Google Scholar 

  17. Samorodnitsky, G., & Taqqu, M. S. (1988). Stable non-Gaussian random processes: stochastic models with infinite variance. London: Chapman & Hall.

    Google Scholar 

  18. Bergstom, H. (1952). On some expansions of stable distribution functions Archiv der Mathematik, 2, 375–378.

    Google Scholar 

  19. Kuruoglu, E. (1998). Signal processing in alpha stable environments: A least l p approach. Ph.D. dissertation, University of Cambridge.

  20. Gonzalez, J., Griffith, D., & Arce, G. (1996). Matched myriad filtering for robust communications. Proc. Conf. on Info. Sciences and Systems.

Download references

Author information

Authors and Affiliations

  1. The University of Texas at Austin, Austin, TX, 78712, USA

    Marcel Nassar, Kapil Gulati, Marcus R. DeYoung & Brian L. Evans

  2. Intel Corporation, Santa Clara, CA, 95054, USA

    Keith R. Tinsley

Authors
  1. Marcel Nassar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kapil Gulati
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marcus R. DeYoung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Brian L. Evans
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Keith R. Tinsley
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kapil Gulati.

Additional information

This research was supported by Intel Corporation.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nassar, M., Gulati, K., DeYoung, M.R. et al. Mitigating Near-field Interference in Laptop Embedded Wireless Transceivers. J Sign Process Syst 63, 1–12 (2011). https://doi.org/10.1007/s11265-009-0350-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11265-009-0350-7

Keywords

Search

Navigation