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
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
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: