Texas Instruments Seminar

Statistical Signal Processing for Sensing and Mitigating Impulsive Noise in Communication 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, Mr. Alberto Alcocer Ochoa, Ms. Chaitanya Sreerama and Mr. Keith R. Tinsley at Intel Labs

Tuesday, January 12, 2010


Video demonstrations


Electromagnetic interference (EMI) is a key limiting factor in the communication performance of powerline, Wi-Fi, Wimax, cellular and other communication systems. Sources of EMI include

  1. users operating in the same transmission band (e.g. due to spatial reuse in cellular systems)
  2. the computational platform itself (e.g. from driving clocks and their harmonics)
  3. nearby electronic equipment (e.g. from microwave ovens radiating in the 2.4 GHz band)

EMI is commonly modeled as additive impulsive noise. Among the many proposed impulsive noise distributions, we have been using Middleton Class A, Gaussian Mixture and Symmetric Alpha Stable distributions.

In this talk, we focus on EMI at radio frequencies. We assume that radio frequency interference (RFI) has been received by an antenna and downconverted to a discrete-time baseband signal. For discrete-time baseband signals, we present statistical modeling of RFI, validate the models using measured RFI datasets, and propose receiver designs for mitigating RFI. Several proposed designs demonstrate 10x-100x reduction in bit error rate for single-antenna and two-antenna receivers. We demonstrate that the statistical approach models RFI from the computational platform and from users operating in the same transmission band. We are currently generalizing the statistical models to model RFI from nearby electronic equipment.

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



Prof. Brian L. Evans is an 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. (Error diffusion is two-dimensional data conversion by sigma-delta modulation.) He has graduated 16 PhD students and published more than 180 refereed conference and journal papers. He received a 1997 National Science Foundation CAREER Award.

Mail comments about this page to bevans@ece.utexas.edu.