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== Summer of Code 2020: Project ideas list ==
Note- also check out [[Grant Ideas]] for additional ideas that are more suited towards grant money than GSoC.


This is the list of project ideas for the summer of code 2019 within GNU Radio.<br />
 
== Summer of Code 2023: Project ideas list ==
 
This is the list of project ideas for the summer of code 2023 within GNU Radio.<br />
Remember that these are '''ideas''' and are merely meant as an inspiration for you to write your own proposal.
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 [http://gnuradio.org/redmine/projects/gnuradio/wiki/MailingLists 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.
Students who do not find a fit among these projects are encouraged to engage with us and suggest new ones. The [[MailingLists|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 [https://developers.google.com/open-source/gsoc/faq Google GSoC FAQ] page for a broader understanding of project, mentor, and student responsibilities is recommended.
Reviewing the [https://developers.google.com/open-source/gsoc/faq Google GSoC FAQ] page for a broader understanding of project, mentor, and student responsibilities is recommended.
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* Not specific to a certain hardware. No specific embedded devices, either, please.
* Not specific to a certain hardware. No specific embedded devices, either, please.
* Both OOTs and in-tree improvements are welcome
* 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
=== 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
=== 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 ===
=== QT Widgets Improvements ===
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This project is cleanly divided into several sub-projects:
This project is cleanly divided into several sub-projects:


* Add new widgets
* Add a new widget
** Compass display (e.g. for direction-finding applications)
** Compass display (e.g. for direction-finding applications)
** MPEG display (e.g. for video demod output)
** MPEG display (e.g. for video demod output)
Line 129: Line 45:


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


'''Mentor(s)'''
'''Project length'''
 
350 hours


Tim O'Shea
'''Difficulty'''


Hard


'''Mentor(s)'''


=== Standardized High Throughput FEC Codes ===
Andrej Rode


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'''
=== GPU Accelerated Signal Processing Blocks ===


* Understanding of ''gr-fec'' API. Knowledge on channel coding. Understanding of C++.
GPUs offer incredible capability for accelerating a number of signal processing routines when the calculations can be done in parallel. Also, GNU Radio 3.10 brought in a "custom buffers" feature which provides support generally for accelerator devices by allowing blocks to have direct access to device memory, finally making accelerator processing feasible through a flowgraph (see [https://fosdem.org/2022/schedule/event/radio_gr3_10/ FOSDEM 2022 Presentation].


'''Outcome'''
One piece that is missing for GNU Radio is a library of blocks that accelerate common DSP routines.  There are several interesting libraries of GPU accelerated signal processing - primarily using CUDA because of its accessible programming paradigm and the ubiquity of NVIDIA hardware:


* Standardized Codes, e.g. LTE Turbo Codes, 5G Polar Codes, 5G LDPC Codes, CCITT Convolutional Codes etc. are available in ''gr-fec''.
* [https://github.com/NVIDIA/MatX Matx]
* The preferred goal is to find a highly optimized implementation and integrate these into GNU Radio.
* [https://github.com/rapidsai/cusignal cuSignal] (Python signal processing)
* [https://github.com/gnuradio/cusp CUSP]


'''Mentor(s)'''
Integration of any of this functionality, along with additional kernels for signal processing would need to be predicated on using [https://github.com/gnuradio/gr-cuda gr-cuda] custom buffers, and expanding this module as needed


* Johannes Demel
This project can be broken into several subprojects:


* Create gr-matx OOT
** Add Matx Custom Buffer Type (after gr-cuda)
** Create blocks wrapping Matx operations
* Expand gr-cuda
** Additional custom buffer types - pinned, unified
** Create python custom buffers allowing zero copy into python blocks
* Create gr-cuSignal
** Wrap cuSignal functionality (dependent on python zero copy)
* Replicate existing GR blocks as CUDA accelerated (things not in cuSignal or Matx)
** Target for extensions to Matx, cuSignal, or CUSP (within our control)
** FIR Filters
** Polyphase Resampler
** Signal Source
** Moving Average
** Polyphase Clock Sync
** Stream Operators
** ...


'''Prerequisites'''


=== Android ===
* Knowledge of C++ and Python.
* Familiarity with CUDA programming


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.
'''Project length'''


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):
350 hours


* Improve support for development environment
'''Difficulty'''
** 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 params (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]]
Medium


'''Prerequisites'''
'''Mentor(s)'''


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


'''Mentor(s)'''


* Ben Hilburn
=== GRC: Standalone application and pluggable workflows ===


GNU Radio Companion (GRC) has become useful outside of just GNU Radio, and several projects have forked and maintained their own versions.  Even within GRC, there are different workflows (QT GUI, C++, Bokeh-gui) with different options in the path to render a working flowgraph see [https://github.com/gnuradio/greps/blob/main/grep-0025-grc-out-of-tree.md GREP 0025].  In its most basic form, GRC does the following:


* User sets high level options (type of flowgraph)
* User draws flowgraph graphically with blocks and connections
* Flowgraph uses templates (Mako) to render to a python script


=== Filter Design Tool Enhancements ===
The goal of this project is to pull GRC out of the GNU Radio codebase and make the workflow modular.  There should be a high level selection of the workflow that defines the options block.  In our current usage these workflows could be:


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.
* Python QT GUI
* C++ QT GUI
* Python No GUI
* C++ No GUI
* Bokeh GUI


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:
The workflow should map to a set of templates that are used to render the output script.  The definition of the workflow options and the associated templates should be defined in some pluggable manner (files dropped into a directory that GRC sees at runtime), so that "out of tree" workflows can be added easily - because we don't know all the use cases of GRC.


* When used in GRC, we want to save the results of the tool in a local file or for use in actual blocks.
'''Steps'''
* It still currently runs on PyQWT, which is obsolete and needs to be updated to QT4/QT5
* Move GRC as a separate repository (while maintaining git history)
** See https://github.com/trondeau/gnuradio/tree/filter/design_tool_newgui
* Remove dependence of GRC on gnuradio
* Add more support for filter design concepts and other filters.
* Modularized options block
** Cascaded filters
* Modularized templates
** Better support for creating PFB filters
* Allow templating with jinja as well
* If time allows:
** Modularize gr-modtool templates as well per [https://github.com/gnuradio/greps/blob/main/grep-0026-modtool-template-rework.md GREP 0026]
** Support multiple domains' workflows.


'''Prerequisites'''
'''Prerequisites'''


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


'''Mentor(s)'''
'''Project length'''


* Marcus Leech
350 hours


'''Difficulty'''


Medium


=== Implement SigMF functionality for GNU Radio ===
'''Mentor(s)'''


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.<br />
Josh Morman,
SigMF is specified and has a minimal reference implementation here: https://github.com/gnuradio/sigmf
Håkon Vågsether,
Sebastian Koslowski,
?? Someone else that is a GRC Wizard


GNU Radio needs its own implementation of SigMF that ties into the block structure. The following things need to be written:
=== GRC: Build-in sub flowgraphs ===


* Source and Sink blocks for SigMF (similar to the current metadata blocks)
GNU Radio has hierarchical blocks as a way 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. 
* Converters for files generated with the current metadata file formats
* Static analysis tools using SigMF


'''Prerequisites'''
'''Prerequisites'''


* Basic understanding of how to write GNU Radio blocks is required.
* GRC is written in Python which is (almost) all you need to know for this project.
* Also, the student needs to explain that she or he has understood the concepts of SigMF, although SigMF is a very simple, JSON-based file format.
* Depending on the precise path that the student and the mentor define, experience in GUI development would also be useful.


'''Outcome'''
'''Outcome'''


* The source and sink blocks are by the far the most important outcomes of this project. We estimate it would take about a third of the active coding time to implement those, and have them merged around the midterms.<br />
* A vastly improved workflow for structuring flowgraphs
This leaves plenty of time for further development.
 
* The next most important task are the converters, so existing metadata files will continue to be useful. After that, the student should define own tasks based on their interests. A very relevant problem is the ability to effectively visualize metadata in combination with signals.
'''Project length'''
 
175 hours
 
'''Difficulty'''
 
Easy


'''Mentor(s)'''
'''Mentor(s)'''


* Bastian Bloessl, Sebastian Müller
Håkon Vågsether
 




=== Statistical Toolbox for GRC ===
=== Revitalize old modules ===


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 datascience analysis and modeling on signal data.
Some of the in-tree modules are in need of attention. For example, gr-wavelet does not have any examples, and several of the tests in gr-trellis are failing.  


'''Prerequisites'''
'''Prerequisites'''


* Understanding of existing GNU Radio tools (e.g., GRC), GNU Radio Out-of-Tree Modules, and statistics / datascience modeling.
* Knowledge of C++, Python and DSP.


'''Outcome'''
'''Outcome'''


* An OOT module that provides statistical analysis capabilities for GNU Radio.
* More example code, tests and flowgraphs for various in-tree modules


'''Mentor(s)'''
'''Project length'''


* Ben Hilburn
175 hours


'''Difficulty'''


Easy


=== Digital Pre-Distortion ===
'''Mentor(s)'''


Digital Pre-Distortion (DPD) is a technique allowing transmitters to compensate for non-linear responses in their hardware, most notably the power amplifier. This improves SNR and can allow more spectral and power efficient operation of a given set of hardware.
Håkon Vågsether, ?


DPD is widely used and is increasingly necessary as many multicarrier signals such as what are seen in DVB and LTE exhibit high peak to average power ratios (PAPRs). DPD implementations are not widely available in the open source community. This is a deficit that this project hopes to correct. Over the course of the project the student would implement standard DPD algorithms in to a GNU Radio out of tree module so that they can be available for use directly or as reference designs.
 
=== CI for maintenance branches and select OOT modules ===
 
It would be useful to have nightly builds for GNU Radio's maintenance branches (3.8, 3.9, 3.10) and some select OOTs.  


'''Prerequisites'''
'''Prerequisites'''


* Workable C++ proficiency, basic knowledge of radio systems, ideally familiarity with GNU Radio and/or Digital Pre-Distortion
* Experience with Docker?
* ?


'''Outcome'''
'''Outcome'''


* Implement standard memory-less and memory based DPD algorithms
* Automated PPAs, Snaps, Flatpak apps
* Implement the training algorithms for such DPD application algorithms.
* Implement a GUI tool or testbench for viewing the AM-AM and AM-PM responses of an amplifier


'''Mentor(s)'''
'''Project length'''
 
175 hours
 
'''Difficulty'''


* Derek Kozel
Easy


'''Mentor(s)'''


Håkon Vågsether, ?


== Application process ==
== Old Ideas ==


Students interested in participating, read the [[GSoCStudentInfo|student instructions]] and the [[GSoCManifest|rules of conduct]].
Feel free to browse [https://wiki.gnuradio.org/index.php?title=OldGSoCIdeas old ideas] from previous years for inspiration.
* Please introduce yourself on the [https://lists.gnu.org/mailman/listinfo/discuss-gnuradio 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.

Latest revision as of 19:21, 7 February 2023

Note- also check out Grant Ideas for additional ideas that are more suited towards grant money than GSoC.


Summer of Code 2023: Project ideas list

This is the list of project ideas for the summer of code 2023 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

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.

Project length

350 hours

Difficulty

Hard

Mentor(s)

Andrej Rode


GPU Accelerated Signal Processing Blocks

GPUs offer incredible capability for accelerating a number of signal processing routines when the calculations can be done in parallel. Also, GNU Radio 3.10 brought in a "custom buffers" feature which provides support generally for accelerator devices by allowing blocks to have direct access to device memory, finally making accelerator processing feasible through a flowgraph (see FOSDEM 2022 Presentation.

One piece that is missing for GNU Radio is a library of blocks that accelerate common DSP routines. There are several interesting libraries of GPU accelerated signal processing - primarily using CUDA because of its accessible programming paradigm and the ubiquity of NVIDIA hardware:

Integration of any of this functionality, along with additional kernels for signal processing would need to be predicated on using gr-cuda custom buffers, and expanding this module as needed

This project can be broken into several subprojects:

  • Create gr-matx OOT
    • Add Matx Custom Buffer Type (after gr-cuda)
    • Create blocks wrapping Matx operations
  • Expand gr-cuda
    • Additional custom buffer types - pinned, unified
    • Create python custom buffers allowing zero copy into python blocks
  • Create gr-cuSignal
    • Wrap cuSignal functionality (dependent on python zero copy)
  • Replicate existing GR blocks as CUDA accelerated (things not in cuSignal or Matx)
    • Target for extensions to Matx, cuSignal, or CUSP (within our control)
    • FIR Filters
    • Polyphase Resampler
    • Signal Source
    • Moving Average
    • Polyphase Clock Sync
    • Stream Operators
    • ...

Prerequisites

  • Knowledge of C++ and Python.
  • Familiarity with CUDA programming

Project length

350 hours

Difficulty

Medium

Mentor(s)

Josh Morman


GRC: Standalone application and pluggable workflows

GNU Radio Companion (GRC) has become useful outside of just GNU Radio, and several projects have forked and maintained their own versions. Even within GRC, there are different workflows (QT GUI, C++, Bokeh-gui) with different options in the path to render a working flowgraph see GREP 0025. In its most basic form, GRC does the following:

  • User sets high level options (type of flowgraph)
  • User draws flowgraph graphically with blocks and connections
  • Flowgraph uses templates (Mako) to render to a python script

The goal of this project is to pull GRC out of the GNU Radio codebase and make the workflow modular. There should be a high level selection of the workflow that defines the options block. In our current usage these workflows could be:

  • Python QT GUI
  • C++ QT GUI
  • Python No GUI
  • C++ No GUI
  • Bokeh GUI

The workflow should map to a set of templates that are used to render the output script. The definition of the workflow options and the associated templates should be defined in some pluggable manner (files dropped into a directory that GRC sees at runtime), so that "out of tree" workflows can be added easily - because we don't know all the use cases of GRC.

Steps

  • Move GRC as a separate repository (while maintaining git history)
  • Remove dependence of GRC on gnuradio
  • Modularized options block
  • Modularized templates
  • Allow templating with jinja as well
  • If time allows:
    • Modularize gr-modtool templates as well per GREP 0026
    • Support multiple domains' workflows.

Prerequisites

  • Knowledge of Python.

Project length

350 hours

Difficulty

Medium

Mentor(s)

Josh Morman, Håkon Vågsether, Sebastian Koslowski, ?? Someone else that is a GRC Wizard

GRC: Build-in sub flowgraphs

GNU Radio has hierarchical blocks as a way 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

Project length

175 hours

Difficulty

Easy

Mentor(s)

Håkon Vågsether


Revitalize old modules

Some of the in-tree modules are in need of attention. For example, gr-wavelet does not have any examples, and several of the tests in gr-trellis are failing.

Prerequisites

  • Knowledge of C++, Python and DSP.

Outcome

  • More example code, tests and flowgraphs for various in-tree modules

Project length

175 hours

Difficulty

Easy

Mentor(s)

Håkon Vågsether, ?


CI for maintenance branches and select OOT modules

It would be useful to have nightly builds for GNU Radio's maintenance branches (3.8, 3.9, 3.10) and some select OOTs.

Prerequisites

  • Experience with Docker?
  • ?

Outcome

  • Automated PPAs, Snaps, Flatpak apps

Project length

175 hours

Difficulty

Easy

Mentor(s)

Håkon Vågsether, ?

Old Ideas

Feel free to browse old ideas from previous years for inspiration.

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