Intel Labs Seminar

Mitigation of Radio Frequency Interference From the Computer Platform to Improve Wireless Data Communications

Prof. Brian L. Evans
Embedded Signal Processing Laboratory
Dept. of Electrical and Computer Engineering
The University of Texas at Austin, Austin, Texas

Collaboration with graduate students Kapil Gulati and Marcel Nassar and
undergradate students Navid Aghasadeghi and Arvind Sujeeth.

Monday, April 16, 3:30 PM
Intel Labs, Portland, Oregon



This presentation is intended to convey preliminary results and seek feedback on our project to reduce radio frequency interference (RFI) experienced by wireless data communication transceivers deployed in computing platforms. In particular, the project targets RFI generated by the computing platform itself. In the platform, relevant sources of RFI include PCI express busses, memory subsystems, processors, LCD displays and SATA busses.

RFI may be viewed as a combination of independent radiation events, and predominantly has non-Gaussian statistics. We model the non-Gaussian statistics using Middleton Class A and B models and alpha-stable processes. From simulated data, we can estimate the parameters of a Class A model and an alpha-stable process using previously published results running on desktop processors and in floating-point arithmetic. The parameters can then be used to reduce the noise or aid in improved detection of a signal plus RFI.

Future work is to develop desktop (floating-point) and embedded (fixed-point) parameter estimation methods for Class B models, and embedded parameter estimation methods for Class A and B models, alpha-stable processes, and mixtures of alpha-stable processes. Future work is also to develop desktop and embedded implementations of detection methods for a signal plus RFI.


Prof. Brian L. Evans is a Professor of Electrical and Computer Engineering at The University of Texas at Austin. Prof. Evans' research efforts are in embedded real-time digital signal and image processing systems. His research group derives application performance bounds and optimal algorithms to achieve those bounds, as well as near-optimal low-complexity algorithms and embedded prototypes. His group conducts research in multicarrier wired and wireless data communication systems. In image processing, his group researches high-quality halftoning for desktop printers and perceptual hashing for image databases. Prof. Evans has published over 170 refereed conference and journal papers.

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