Difference between revisions of "GSoCIdeas"
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* Bastian Bloessl
* Bastian Bloessl
=== Filter Design Tool Enhancements ===
=== Filter Design Tool Enhancements ===
Revision as of 16:44, 30 January 2020
- 1 Summer of Code 2020: Project ideas list
- 1.1 GRC: Build-in sub flowgraphs
- 1.2 Qt5 GUI Integrations
- 1.3 GRC: View-Only Mode (Secure)
- 1.4 Extending and Updating gr-radar
- 1.5 QT Widgets Improvements
- 1.6 Standardized High Throughput FEC Codes
- 1.7 Android
- 1.8 Runtime Benchmarks
- 1.9 Filter Design Tool Enhancements
- 1.10 Implement SigMF functionality for GNU Radio
- 1.11 Statistical Toolbox for GRC
- 1.12 Digital Pre-Distortion
- 2 Application process
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.
- GRC is written in Python which is (almost) all you need to know for this project.
- A vastly improved workflow for structuring flowgraphs
- Sebastian Koslowski
Qt5 GUI Integrations
Idea: Wrap the Qt GUI sinks to appear in QtCreator, including the GUI aspects of their parameterization
- C++, Python proficiency
- Qt experienced
- 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
- 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.
- GRC is implemented using Python. So, Python should be known pretty well.
- Safely view other people's flowgraphs without putting your PC at risk.
- 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
- 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.
- 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.
- 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
- Familiarity with QT is essential.
- Widgets are written in C+, so some C+ knowledge is also required.
- Python skills are highly useful.
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.
- Understanding of gr-fec API. Knowledge on channel coding. Understanding of C++.
- 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.
- Johannes Demel
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
- Some Android experience
- Enjoy writing GUI widgets
- C++/Java experience
- Bastian Bloessl
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.
- C++ programming
- Data evaluation and visualization
- Automation tools (like GNU Make to run benchmarks)
- 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
- Add more support for filter design concepts and other filters.
- Cascaded filters
- Better support for creating PFB filters
- Strong DSP background required.
- Python and QT knowledge highly useful (at least one of those is a must).
- Marcus Leech
Implement SigMF functionality for GNU Radio
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
GNU Radio needs its own implementation of SigMF that ties into the block structure. The following things need to be written:
- Source and Sink blocks for SigMF (similar to the current metadata blocks)
- Converters for files generated with the current metadata file formats
- Static analysis tools using SigMF
- Basic understanding of how to write GNU Radio blocks is required.
- 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.
- 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.
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.
- Bastian Bloessl, Sebastian Müller
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.
- Understanding of existing GNU Radio tools (e.g., GRC), GNU Radio Out-of-Tree Modules, and statistics / data-science modeling.
- An OOT module that provides statistical analysis capabilities for GNU Radio.
- Ben Hilburn
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.
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.
- Workable C++ proficiency, basic knowledge of radio systems, ideally familiarity with GNU Radio and/or Digital Pre-Distortion
- Implement standard memory-less and memory based DPD algorithms
- 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
- Derek Kozel
- 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.