Bit-Error-Rate (BER) Predict using Neural Network

Aug, 2019
Jet Yu, [email protected]
Hussein Metwaly Saad, [email protected]
Yue Xu, [email protected]
Mike Buehrer, [email protected]
Wireless, ECE, Virginia Tech

Dataset

under folder DATA, for more data, click DataSet, and ./DATA/READ.md describe the data.

How to run

if need, run ./FUNCTION/mainData.m to generate dataset
Neural Network
- main_regression.py, where labels are in [0,1] scale
- main_regression_dB.py, where labels are in log scale, [0, 40]dB
- main_classification.py, where labels are in another log scale
Random Forest
- mainRF.m, in matlab. 1-dimension
- mainRF.py, in python

File Description

ToolBox.py is called by main_classification.py.
Under FUNCTIONS run mainGenerateData.m to generate traing dataset.
Result folder has all trained results when run main*.py file
Predict folder has all test results when run test.py

Chat/ Hangout Group

Chat/ Hangout Group

Slides

performance Google slides

News

(Sep 29) starter code online

Roadmap

Config

running on ARC VT is prefered, run python is preferred.

Python
- tensorflow, Keras, scikitlearn

Running Time Reference