Journal of Signal Processing Systems, April 2011, vol. 63, no. 1, pp. 1-12, invited paper. (First appeared online on March 27, 2009.)

Mitigating Near-Field Interference in Laptop Embedded Wireless Transceivers

Marcel Nassar (1), Kapil Gulati (1), Marcus DeYoung (1), Brian L. Evans (1) and Keith R. Tinsley (2)

(1) Department of Electrical and Computer Engineering, Engineering Science Building, The University of Texas at Austin, Austin, TX 78712 USA
nassar.marcel@mail.utexas.edu - gulati.k@gmail.com - marcus.deyoung@gmail.com - bevans@ece.utexas.edu

(2) System Technology Lab, Intel, Hillsborough, Oregon USA.

Paper Draft

RFI Modeling and Mitigation Toolbox

RFI Mitigation Research at UT Austin

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 (SaS) models. The contributions of this paper are to evaluate
  1. the performance vs. complexity of parameter estimation algorithms,
  2. the closeness of fit of parameter estimation algorithms to measured RFI data from the computer platform,
  3. the communication performance vs. computational complexity tradeoffs for the correlation receiver, Wiener filter, and Bayesian detector,
  4. the performance of myriad filtering in combating RFI interference modeled as SaS interference, and
  5. performance under real measured noise samples.

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Last Updated 01/31/16.