of Signal Processing Systems, Mar. 2009, invited paper.
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
(2) System Technology Lab, Intel, Hillsborough, Oregon USA.
RFI Modeling and
RFI Mitigation Research at UT Austin
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
- the performance vs. complexity of parameter estimation algorithms,
- the closeness of fit of parameter estimation algorithms to measured
RFI data from the computer platform,
- the communication performance vs. computational complexity tradeoffs
for the correlation receiver, Wiener filter, and Bayesian detector,
- the performance of myriad filtering in combating RFI interference
modeled as SaS interference, and
- performance under real measured noise samples.
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