According to the rules of conduct, the milestones concerning this project must be publicly available. The Milestones are listed below. Any changes will be discussed and reviewed by my mentors.

**Midterm update**

Since another student, Christopher Richardson, was accepted to work on this project, my milestones were altered together with my mentors. Since Chris has taken over the AMC part which was planned for my second half of GSoC, I am now developing a OFDM estimation block for this toolbox instead.

Midterm Milestones

  • Prototype signal detection algorithms in python and evaluate best approach to implement
  • Implement signal detection algorithm in C++ and wrapping it in a new block
  • Create first GUI with QWT and QT with graphical feedback of signal detection block
  • Verification with over-the-air signals
  • Documentation for the mentioned components

Final Milestones

  • Prototype modulation classification algorithms including tensorflow and cyclostationary feature analysis
  • Implement automatic modulation classification (AMC) blocks in C++ (cyclostationary) and python (tensorflow)
  • Design and implement an OFDM parameter estimation block in C++
    • Estimate subcarrier spacing, symbol time, FFT size, timing offset and frequency offset
    • Correct timing and frequency offset
  • Extend GUI to final form and include feedback of AMC and OFDM block
  • Verification with over-the-air signals
  • Finish documentation
  • Create example flowgraphs for whole toolbox functionality
  • Publish module on CGRAN (or include it in main tree)

Optional Milestones

  • Create automatic demodulation block prototype for AM/FM modulation schemes
  • Include demod possibility in GUI