Radio Frequency Interference Sensing and Mitigation in Wireless Receivers

Prof. Brian L. Evans
Dept. of Electrical and Computer Engineering
Wireless Networking and Communications Group
The University of Texas at Austin, Austin, Texas

Lead graduate students: Aditya Chopra, Kapil Gulati and Marcel Nassar

Research performed in collaboration with Xintian Eddie Lin, Chaitanya Sreerama, Keith R. Tinsley (technical lead) and Jorge Aguilar Torrentera at Intel Labs

Monday, March 16, 2009


Video Demonstration (19 MB)


Wireless data communication transceivers deployed on a computation platform, e.g. a laptop or desktop computer, are greatly affected by the radio frequency interference (RFI) generated by the platform itself. Interfering sources include not only clocks and busses, but also power saving subsystems. The problem has intensified due to increasing complexity of computational platforms, decreasing form factors and increasing numbers of wireless transceivers on the platform.

In this talk, we present statistical modeling of RFI by the platform and receiver design for mitigating that RFI. In particular, we use Middleton Class A and symmetric alpha stable models to capture the impulsive characteristics of RFI. We evaluate the applicability of these models using measured interference datasets obtained from Intel. Several filtering and detection methods are discussed for single- and two-antenna receivers in the presence of non-Gaussian impulsive interference. We demonstrate 1-2 orders of magnitude reduction in bit error rate at the same transmission rate, and evaluate the design tradeoffs of our proposed RFI sensing and mitigation techniques. We also discuss the applicability of these proposed techniques to other forms of RFI, particularly co-channel interference in cellular networks.

Our RFI sensing and mitigation methods are available in a free Matlab toolbox:


Prof. Brian Evans was recently elevated to IEEE Fellow "for contributions to multicarrier communications and image display". In multicarrier communications, his group developed the first linear complexity algorithm that allocates resources to optimize bit rates in multiuser OFDM systems (for cellular and WiMax) and is realizable in fixed-point hardware/software. His group also developed the first ADSL equalizer training method that maximizes a measure of bit rate and is realizable in real-time fixed-point software. In image display, his group's primary contribution is in the design, analysis, and quality assessment of halftoning by error diffusion for real-time processing by printer pipelines. He has published over 180 refereed conference and journal papers. He has graduated 16 PhD students, including Dr. Kyungtae Han at Intel Labs.

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