Mitigating Near-field Interference in Laptop Embedded Wireless Transceivers

  • Authors:

  • Marcel Nassar;Kapil Gulati;Marcus R. Deyoung;Brian L. Evans;Keith R. Tinsley

  • Affiliations:

  • The University of Texas at Austin, Austin, USA 78712;The University of Texas at Austin, Austin, USA 78712;The University of Texas at Austin, Austin, USA 78712;The University of Texas at Austin, Austin, USA 78712;Intel Corporation, Santa Clara, USA 95054

  • Venue:
  • Journal of Signal Processing Systems
  • Year:
  • 2011

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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驴驴驴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 驴S) 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 驴S interference, and (5) the approximations to filtering and detection methods developed to mitigate RFI for a computationally efficient implementation.