Demo Title : Radio Frequency Interference Modeling and Mitigation in SISO Systems
File Name  : RFI_DemoModelingAndMitigation.m

This demo provides a simulation environment to statistically model and mitigate Radio Frequency Interference (RFI) in single input single output systems. The demo can be used as a tool to statistically model measured interference dataset, evaluate goodness-of-fit for these statistical-physical models, and evaluate the performance of various receiver techniques to mitigate RFI.

Following are the steps required to run the demo.

STEP 1: 
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Choose the generating source of RFI from the 'RFI Generation' panel. The user can choose measured dataset stored in a text file or use a synthetically generated RFI data using different RFI models.

For synthetic data generation, we provide typical values of the parameters for different statistical models based on the RFI environment desired by the user. These can be chosen by selecting 'highly impulsive', 'moderately impulsive', or 'nearly Gaussian' RFI environment in the 'RFI Generation' panel.

STEP 2: 
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Choose different RFI models used to fit the data from the 'Statistical Modeling' panel. In addition, the user may want to modify some parameters for calculating the empirical and estimating model densities. These include:
  
a) Number of Symbols: Number of measured or synthetic interference symbols used for generating the empirical PDF and parameter estimation of statistical models.

b) xmax: The empirical and estimated probability density functions (PDF) are calculated in the range (-xmax, xmax). 

c) Resolution: The empirical and estimated PDFs are calculated at 'Resolution' number of points in the range (-xmax, xmax).

STEP 3:
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From the 'Receiver Design to Mitigate RFI', choose various receiver structures to evaluate the relative communication performance of various RFI mitigation techniques. The performance of the receivers are evaluated by using synthetically generated or measured RFI data based on the selection in 'RFI Generation' panel. The receivers estimate the interference parameters of the statistical model for which they are designed for, using training symbols specified in Step 2. 

STEP 4: 
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Run the simulation using the 'Start Simulation' button.
        
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Copyright (c) The University of Texas
Please see the file Copyright.txt that came with this release for details
Programmers: Kapil Gulati   (gulati@ece.utexas.edu)

Revisions:
Date         Version	Owner	Comments
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04/10/10     1.4.1 Beta	gulati	Initial creation
12/14/10     1.6 Beta	gulati	Added tooltips

