GSoCIdeas

Summer of Code 2021: Project ideas list
This is the list of project ideas for the summer of code 2021 within GNU Radio.

Remember that these are ideas and are merely meant as an inspiration for you to write your own proposal.

Students who do not find a fit among these projects are encouraged to engage with us and suggest new ones. The GNU Radio discussion mailing list is the best place to contact all of us. Please do not contact us off-list for the sake of discussing the summer of code, unless you're contacting a mentor listed here to get feedback on a proposal.

Reviewing the Google GSoC FAQ page for a broader understanding of project, mentor, and student responsibilities is recommended.

If you need a USRP or other radio hardware to complete the project, we will be able to arrange something.

Please add ideas to this list (you may cannibalize old ideas, of course!).

Guidelines for good projects (when suggesting projects, please consider these):


 * Clearly defined scope, with a main target that can be done in 3 months at 50% capacity
 * Clear benefits for the GNU Radio project
 * Not specific to a certain hardware. No specific embedded devices, either, please.
 * Both OOTs and in-tree improvements are welcome

The time a student can spend on a GSoC project has been reduced by 50% for 2021 - keep this in mind when submitting your ideas

QT Widgets Improvements
The gr-qtgui in-tree component provides some QT widgets for signal visualization. This component needs some improvement to become more useful.

This project is cleanly divided into several sub-projects:


 * Add a new widget
 * Compass display (e.g. for direction-finding applications)
 * MPEG display (e.g. for video demod output)
 * Matrix sink (e.g. for radar Doppler/range plane visualization, or 2D-equalizer taps visualization)


 * Improve current widgets
 * Better code structure to make the current widgets more manageable, extensible and remove code duplication between widgets
 * More Control Panels on other widgets (follow lead on the frequency sink)
 * Improve UI, make more intuitive, more power to mouse users
 * Set trigger point with mouse


 * Integration / Support for QT Creator
 * QML design
 * Allow to build full GUI applications from, say, GRC

Prerequisites


 * Familiarity with QT is essential.
 * Widgets are written in C++, so some C++ knowledge is also required.
 * Python skills are highly useful.

Mentor(s)

Andrej Rode

Standardized High Throughput FEC Codes
Channel coding is essential to modern communications. Also, it is computationally very heavy. As of now, there exist implementations in GNU Radio which are too slow to be integrated into high throughput applications. GNU Radio would benefit from integration of standardized decoders for Turbo and LDPC codes. These codes would only support a certain subset of the whole code class but would be well optimized.

Prerequisites


 * Understanding of gr-fec API. Knowledge on channel coding. Understanding of C++.

Outcome


 * Standardized Codes, e.g. LTE Turbo Codes, 5G Polar Codes, 5G LDPC Codes, CCITT Convolutional Codes etc. are available in gr-fec.
 * The preferred goal is to find a highly optimized implementation and integrate these into GNU Radio.

Mentor(s)


 * Johannes Demel

GRC: View-Only Mode (Secure)
When a flowgraph from an untrusted source is opened if GRC, arbitrary Python code can be executed. This poses a potential security risk. Storing the all evaluated values of all parameters within a flow graph (.grc) file would allow us to open such flow graphs without compromising security. No code would be have to executed to draw the flow graph and block parameters can be viewed safely. Only if the flow graph is modified the user would have to choose to trust the flow graph thus enabling normal eval operations.

Prerequisites


 * GRC is implemented using Python. So, Python should be known pretty well.

Outcome


 * Safely view other people's flowgraphs without putting your PC at risk.

Mentor(s)


 * Sebastian Koslowski

gr-satellites: Viterbi decoder for 8b10b and FOX satellite decoder
Even though the 8b10b line coding is primarily used for byte-level synchronization and spectral shaping, it adds some redundancy to the data, so it can be used as a forward error correction method to fix some bit errors in the received data. From the perspective of the decoder there is one bit of hidden state, so 8b10b line coding is amenable to Viterbi decoding, as hinted in this document about the AMSAT FOX satellites. One goal of this project is to create Viterbi decoder block(s) for 8b10b and possibly other similar line codes, so that these blocks can be eventually upstreamed in-tree. The error correction performance of this method will be studied using simulations with these blocks. The second goal is to use the Viterbi decoder and gr-satellites to create a full decoder for the FOX satellites from AMSAT.

Prerequisites


 * Knowledge of C++ and Python. Some basic understanding about FEC in general.

Outcome


 * Viterbi decoder block(s) for 8b10b and similar line codes, FOX satellite decoder added to gr-satellites

Mentor(s)


 * Daniel Estévez

Runtime Benchmarks
To facilitate development of a more modern GNU Radio runtime and scheduler, we need a tool to measure its performance (in terms of delay and throughput). This data is required to compare alternate approaches and to become aware of performance regressions early in the process.

The goal of the project is to provide a tool to benchmark the GNU Radio runtime. Since we are interested in the performance on many platforms and architectures, it should provide an option to submit performance data to our server, allowing us to crowdsource data. (Similar to our online stats for SIMD performance.)

Outcome


 * Come up with interesting metrics and, if needed, implement blocks to extract them.
 * Come up with interesting flowgraph topologies that should be benchmarked.
 * Set up automated experiments that iterate over a given parameter space (repetitions, number of samples, size of the flowgraph).
 * Parse, evaluate, and visualize the data.
 * Add an option to upload the performance data to our web server.

Prerequisites


 * C++ programming
 * Data evaluation and visualization
 * Automation tools (like GNU Make to run benchmarks)

Mentor(s)


 * Bastian Bloessl

Summer of Code 2020: Project ideas list
This is the list of project ideas for the summer of code 2020 within GNU Radio.

Remember that these are ideas and are merely meant as an inspiration for you to write your own proposal.

Students who do not find a fit among these projects are encouraged to engage with us and suggest new ones. The GNU Radio discussion mailing list is the best place to contact all of us. Please do not contact us off-list for the sake of discussing the summer of code, unless you're contacting a mentor listed here to get feedback on a proposal.

Reviewing the Google GSoC FAQ page for a broader understanding of project, mentor, and student responsibilities is recommended.

If you need a USRP or other radio hardware to complete the project, we will be able to arrange something.

Please add ideas to this list (you may cannibalize old ideas, of course!).

Guidelines for good projects (when suggesting projects, please consider these):


 * Clearly defined scope, with a main target that can be done in 3 months
 * Clear benefits for the GNU Radio project
 * Not specific to a certain hardware. No specific embedded devices, either, please.
 * Both OOTs and in-tree improvements are welcome

GRC: Build-in sub flowgraphs
GNU Radio has the hierarchical blocks to build reuseable sub flowgraphs. These hier_blocks can be designed in GRC, however, they have to be compiled to code and GRC bindings, before they can be used in other GRC files. While this is great for reuseablity across flowgraphs, it is quite cumbersome when the main use is to structure a single (larger) flowgraph. The goal of this project is to ease this use-case by embedding sub flowgraphs directly in the main GRC file. Instead of creating bindings and code and then parsing them back again, this process shall be done in-place to allow quickly editing sub flowgraphs on-the-fly.

Prerequisites


 * GRC is written in Python which is (almost) all you need to know for this project.

Outcome


 * A vastly improved workflow for structuring flowgraphs

Mentor(s)


 * Sebastian Koslowski

Qt5 GUI Integrations
Idea: Wrap the Qt GUI sinks to appear in QtCreator, including the GUI aspects of their parameterization

Prerequisites


 * C++, Python proficiency
 * Qt experienced

Outcome


 * Qt GUI Sinks usable as widgets in QtCreator (not necessarily already showing an "empty" GUI, just placeholders)
 * Possible to import generate Qt GUI description file (UIC) into GRC
 * Interface to map placeholders from GUI design to Qt GUI sinks in Flow graph
 * Integration of that into GRC-generated Python code

Mentor(s)


 * Marcus Müller & Sebastian "GRC-Man" Koslowski

Extending and Updating gr-radar
gr-radar (https://github.com/kit-cel/gr-radar/) was a great and successful GSoC project that provided a few methods of radar in GNU Radio. This module is heavily used by academics, researchers, cybersecurity folks, and hobbyists. This project would work to improve upon the concepts already in there as well as add more radar techniques.

There are uncountable methods and techniques that could be added to this project, such as:


 * SAR / InSAR methods
 * Better passive radar support
 * Speed camera applications
 * Multi-antenna radar techniques

Prerequisites


 * Signal processing and some radar basics are required.
 * Code is written in C++ with some Python on the side, so the student must be able to handle these languages at the least.

Outcome


 * Based on the student's interest, a subset of the radar techniques listed above (or others) are chosen as milestones for this project.
 * All code must be merged back into gr-radar by the end of the summer.

Mentor(s)


 * Stefan Wunsch, Martin Braun

QT Widgets Improvements
The gr-qtgui in-tree component provides some QT widgets for signal visualization. This component needs some improvement to become more useful.

This project is cleanly divided into several sub-projects:


 * Add new widgets
 * Compass display (e.g. for direction-finding applications)
 * MPEG display (e.g. for video demod output)
 * Matrix sink (e.g. for radar Doppler/range plane visualization, or 2D-equalizer taps visualization)


 * Improve current widgets
 * Better code structure to make the current widgets more manageable, extensible and remove code duplication between widgets
 * More Control Panels on other widgets (follow lead on the frequency sink)
 * Improve UI, make more intuitive, more power to mouse users
 * Set trigger point with mouse


 * Integration / Support for QT Creator
 * QML design
 * Allow to build full GUI applications from, say, GRC

Prerequisites


 * Familiarity with QT is essential.
 * Widgets are written in C+, so some C+ knowledge is also required.
 * Python skills are highly useful.

Mentor(s)

Tim O'Shea

Android
One effort of the past years was to improve Android support for GNU Radio. We're getting to a point where we've figured out how to do it, so the next step is to make it more accessible to users and developers.

The Android ecosystem is an entirely different beast from the rest of GNU Radio. To make writing Android/GR apps easy, the following needs to happen (and shall be part of this project):


 * Improve support for development environment
 * Create Dockers for easy start of development
 * Visualization classes for PSD, spectrogram and oscilloscope
 * Easy reuse in other apps, like the gr-qtgui widgets, but for Android SDKs
 * Interactivity concepts
 * Gestures and config for radio parameters (e.g., freq, gain, bandwidth)
 * Create an example FM receiver app that allows easy channel selection etc. through motions and gestures

You can find a summary of the work that has been done on this (years ago) here: Android

Prerequisites


 * Some Android experience
 * Enjoy writing GUI widgets
 * C++/Java experience

Mentor(s)


 * Bastian Bloessl

Runtime Benchmarks
To facilitate development of a more modern GNU Radio runtime and scheduler, we need a tool to measure its performance (in terms of delay and throughput). This data is required to compare alternate approaches and to become aware of performance regressions early in the process.

The goal of the project is to provide a tool to benchmark the GNU Radio runtime. Since we are interested in the performance on many platforms and architectures, it should provide an option to submit performance data to our sever, allowing us to crowdsource data. (Similar to our online stats for SIMD performance.)


 * Come up with interesting metrics and, if needed, implement blocks to extract them.
 * Come up with interesting flowgraph topologies that should be benchmarked.
 * Setup automated experiments that iterate over a given parameter space (repetitions, number of samples, size of the flowgraph).
 * Parse, evaluate, and visualize the data.
 * Add an option to upload the performance data to our web sever.

Prerequisites


 * C++ programming
 * Data evaluation and visualization
 * Automation tools (like GNU Make to run benchmarks)

Mentor(s)


 * Bastian Bloessl, Marcus Mueller

Filter Design Tool Enhancements
GNU Radio provides many tools to design and use digital filters. Using these tools requires both some expertise in these areas as well as an understanding of the performance on the given platform. One example is the selection between FIR (convolution-based) and FFT (fast convolution-based) filters for different resampling rates. Another example is doing stages of filter decomposition when doing large down-sampling. Included in this is the polyphase filterbanks, which again are provided as primitive blocks that need tweaking to work.

This project is to improve our uses of these tools and blocks to make it more obvious to the users as well as automate some of the decisions for optimally using them. Some pointers:


 * When used in GRC, we want to save the results of the tool in a local file or for use in actual blocks.
 * It still currently runs on PyQWT, which is obsolete and needs to be updated to Qt5
 * See https://github.com/trondeau/gnuradio/tree/filter/design_tool_newgui
 * Add more support for filter design concepts and other filters.
 * Cascaded filters
 * Better support for creating PFB filters

Prerequisites


 * Strong DSP background required.
 * Python and QT knowledge highly useful (at least one of those is a must).

Mentor(s)


 * Marcus Leech

Implement SigMF functionality for the GNU Radio Ecosystem
SigMF is the "Signal Metadata Format" that was defined during the 2017 DARPA Hackfest in Brussels. Its purpose is to annotate raw binary dumps of signals with metadata, thus giving meaning to a raw mass of samples.

SigMF is specified and has a minimal reference implementation here: https://github.com/gnuradio/sigmf There is an out-of-tree module providing SigMF functionality for GNU Radio as well: https://github.com/skysafe/gr-sigmf

However, SigMF is not represented well in the GNU Radio tooling landscape. Therefore, a subset of tools can be extended by SigMF support. Incomplete lists of possible tools benefitting from SigMF support:


 * qgrx (https://github.com/csete/gqrx)
 * inspectrum (https://github.com/miek/inspectrum)

Any additional tools are welcome in a proposal.

Prerequisites


 * Knowledge of the programming language of the covered tools.
 * Hands-on experience with the respective tools.
 * Familiarity with the SigMF specification.

Outcome


 * The tools worked on have capability to load and save files in the SigMF format.
 * Depending on the specific tool, SigMF meta data is displayed within the tool.
 * The number of tools worked on needs to be determined by the student, depending on his/her experience.

Mentor(s)


 * Sebastian Müller, Andrej Rode

Statistical Toolbox for GRC
A statistical toolbox for GRC would enable GUI-based statistical analysis. Currently, such analysis can be done by writing an independent program (e.g., with SciPy), but there is no actual integration with GNU Radio. By developing the statistical toolbox, we provide blocks for probability distribution fitting, hypothesis testing, extracting statistical parameters for one-dimensional as well as multi-dimensional data. This would significantly expand GNU Radio users' ability to perform data-science analysis and modeling on signal data.

Prerequisites


 * Understanding of existing GNU Radio tools (e.g., GRC), GNU Radio Out-of-Tree Modules, and statistics / data-science modeling.

Outcome


 * An OOT module that provides statistical analysis capabilities for GNU Radio.

Mentor(s)


 * Ben Hilburn

Application process
Students interested in participating, read the student instructions and the rules of conduct.
 * Please introduce yourself on the GNU Radio mailing list
 * Fill in the formal application for GNU Radio
 * Pick some items from the list above or feel free to suggest another piece of work relevant to this theme. Give us a detailed, week-by-week plan for completing the task over the summer.