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: Mr. Aditya Chopra, Mr. Kapil Gulati and Mr. Marcel Nassar

Research performed in collaboration with Dr. Xintian Eddie Lin, Ms. Chaitanya Sreerama, Mr. Keith R. Tinsley and Mr. Jorge Aguilar Torrentera at Intel Labs

June 23, 2009


Video demonstrations


Radio frequency interference (RFI) is a key limiting factor in the communication performance of wireless systems. Applications of RFI modeling include sense and mitigate strategies for coexistence of wireless communication systems, as well as sense and avoid strategies for cognitive radio. This talk focuses on sense and mitigate strategies for wireless receivers embedded in notebooks and cell phones.

In notebooks and cell phones, significant sources of RFI come from the computational platform itself, including clock frequencies/harmonics and power saving subsystems. Sources of RFI also include other wireless users and services operating in the same frequency band (co-channel interference). RFI may also arise from radiation from nearby electronic equipment such as microwave ovens.

In this talk, we present statistical modeling of platform RFI, validate the models using measured RFI datasets, and propose receiver designs for mitigating platform RFI. Several receiver designs demonstrate 1-2 orders of magnitude reduction in bit error rate at the same transmission rate for both single-antenna and two-antenna systems. We extend our RFI modeling methods to co-channel interference for cellular systems and wireless sensor networks.

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


Prof. Brian L. Evans was 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 graduated 16 PhD students and published more than 180 refereed conference and journal papers.

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