[[TOC(Other/Summer/2017*, depth=2)]]

= SDR Smart Modem =

== Introduction ==

The Smart Modem is designed to receive any signal from a USRP2, recognize the modulation scheme, and demodulate the signal. It also can be given an analog or digital signal, modulate it using a given scheme, and send it to a USRP2. To find this project, please visit [https://github.com/Avanish14/SmartModem/ the project GitHub.] 

== Background == 

This project utilizes machine learning algorithms to recognize the modulation schemes of incoming signals. We first generated data using GNURadio to collect representative sample vectors of signals modulated with various modulation schemes. Then, we trained a convolutional neural network with this data. The results of the training are shown below: 

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    <td align='center'>Performance of Modulation Scheme Recognition</td>
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The neural network can always detect a signal modulated with a QAM scheme but has trouble determining the specific QAM scheme. Therefore, we use a support vector machine to accompany the neural network when it detects a signal modulated with QAM to find the specific scheme. This SVM determines [https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.kstat.html the 2nd and 4th k-statistic] of the QAM signal to better determine the scheme.
 

To modulate and demodulate the signals, GNURadio scripts are used according to the desired modulation schemes. 
== Tools Used ==

USRP2: Software defined radio 

Quadro K5000: high-end GPU 

GNURadio: SDR Toolkit 

TensorFlow: Neural Network Library 

Keras: High level Neural Network API 

Scikit-learn: Machine Learning Library

== Presentations == 

[https://docs.google.com/presentation/d/1m9rotuVr4hpLpY10MMBGhZTetcKyzV9BF0v6NnRmkjc/edit?usp=sharing Week One]

[https://docs.google.com/presentation/d/1nEzAFW227iqZQlQSqCR4I4HzhQwYi-DRduJD6i7ntRQ/edit?usp=sharing Week Two]

[https://docs.google.com/presentation/d/1UGR-wCjR8GUwFSox5ljbt6E6zZkFVFF-U1Cy-Sc3nkg/edit?usp=sharing Week Three]

[https://docs.google.com/presentation/d/1XyAgdPgiC1NR1tk8_XtX3J916pG3mhQxLxu84l584Xg/edit?usp=sharing Week Four]

[https://docs.google.com/presentation/d/1jRdCbB2hDMHOXRkbJRgn2cik0OHAayGbLOnudCcP03A/edit?usp=sharing Week Five]

[https://docs.google.com/presentation/d/1eGAuI4eXQHe116WpSlT5IU-Q9iIYOJtsy2s4VZc1iME/edit?usp=sharing Week Six]

[https://docs.google.com/presentation/d/1qhJ73yLCRhwp5UXDOw8PaRTNP30N4PJHPC5J8sUzrOQ/edit?usp=sharing Week Seven]

[https://docs.google.com/presentation/d/1ZHFW3yFiQhlixTc8fYEmlTr-PkClrOe5GyDPc-MS-hI/edit?usp=sharing Week Eight]

[https://docs.google.com/presentation/d/1Y9pTFxY1WNoe7iWtB68ckklxPV7BF_02LsgW08adK0c/edit?usp=sharing Week Nine]

[https://docs.google.com/presentation/d/1B56JoLX-Ohv6TZ8DT6Tmnnq8Jk4nVpYodjn6MZw_PhA/edit?usp=sharing Week Ten]

[https://docs.google.com/presentation/d/153AQ9sh_Zh7_buXHPbwW-KhlsyJCBH7v4yLrktg5DSc/edit?usp=sharing Week Eleven]

[https://docs.google.com/presentation/d/1oipH2wTvMcrijJQ4hq9K-w2Ip66EchBDkdOGUokFKd4/edit?usp=sharing Week Twelve]

[https://docs.google.com/presentation/d/15YdWQmidhWBq1kMlEhYAmT0OID3ySTuEabgHzJ2I5Eg/edit?usp=sharing Poster]

== The Team ==


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    <td><center><img src="http://www.orbit-lab.org/raw-attachment/wiki/Other/Summer/2017/SpectrumClassification/avanish.png" height=300 hspace="100"></center></td>
    <td><center><img src="http://www.orbit-lab.org/raw-attachment/wiki/Other/Summer/2017/SpectrumClassification/brendan.png" height=300 hspace="100"></center></td>
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    <td align='center'>Avanish Mishra</td>
    <td align='center'>Brendan Bruce</td>
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