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The University of Texas at Austin
Preliminary Results Mitigating Computer Platform Radio Frequency Interference in Embedded Wireless Transceivers Prof. Brian L. Evans The University of Texas at Austin October 17, 2007
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Computer Platform RFI Clocks, clock harmonics, and busses generate RFI
Impulsive in nature (non-Gaussian) Reduces communication performance for embedded wireless data transceivers Goals Improve communication performance in presence of computer platform RFI Develop offline and online algorithms Approaches Statistical modeling of RFI Filtering/detection using estimation of statistical model parameters We’ll be using “interference” and “noise” interchangeably in this talk.
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Statistical Models Middleton Class A Symmetric Alpha Stable
Power Spectral Density Power Spectral Density with A = 0.15 and G = 0.1 with a = 1.5, d = 0 and g = 10
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Middleton Class A Noise
Communication Performance Class A Parameters A = 0.35 G = 0.5 × 10-3
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Symmetric Alpha Stable Noise
Communication Performance SαS Parameters α = 1.5 δ = 0 γ = 1
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Symmetric Alpha Stable Noise
80,000 data samples collected using 20 GSPS scope Parameter Estimation Localization (δ) Dispersion (γ) 0.5833 Characteristic Exponent (α) 1.5525 fX(x) - PDF Normalized MSE x – noise amplitude
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Conclusion Modeling computer platform RFI using impulse noise models promising Middleton Class A: 25 dB gain for BER 10-2 Symmetric Alpha Stable: 5 dB gain for BER 10-1 Tractable parameter estimation algorithms Middleton Class A: iterative + polynomial rooting Symmetric Alpha Stable: non-iterative UT Austin RFI Mitigation Toolbox Research began January 2007: more to come!
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References D. Middleton, “Non-Gaussian noise models in signal processing for telecommunications: New methods and results for Class A and Class B noise models”, IEEE Trans. Info. Theory, vol. 45, no. 4, pp , May 1999. S. M. Zabin and H. V. Poor, “Efficient estimation of Class A noise parameters via the EM algorithms”, IEEE Trans. Info. Theory, vol. 37, no. 1, pp , Jan G. A. Tsihrintzis and C. L. Nikias, "Fast estimation of the parameters of alpha-stable impulsive interference", IEEE Trans. Signal Proc., vol. 44, Issue 6, pp , Jun A. Spaulding and D. Middleton, “Optimum Reception in an Impulsive Interference Environment-Part I: Coherent Detection”, IEEE Trans. Comm., vol. 25, no. 9, Sep A. Spaulding and D. Middleton, “Optimum Reception in an Impulsive Interference Environment-Part II: Incoherent Detection”, IEEE Trans. Comm., vol. 25, no. 9, Sep B. Widrow et al., “Principles and Applications”, Proc. of the IEEE, vol. 63, no.12, Sep J. G. Gonzalez and G. R. Arce, “Optimality of the Myriad Filter in Practical Impulsive-Noise Environments”, IEEE Transactions on Signal Processing, vol 49, no. 2, Feb
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