I'm going to start off by saying that I'm very new to SDR and GNU Radio. This may be a dumb question, but I have been googling and testing things for about two months now trying to get this to work without success. Any help or pointers would be appreciated!
I'm attempting to use GNU Radio 3.8 to transfer a file using differential QPSK. I've tried to follow the tutorials on the wiki as well as several similar academic papers I found on the internet (which also seem to be based off the wiki tutorial). None of them worked on their own but combining what actually works from each one, I managed to create a flowgraph sans hardware that does indeed send and receive the data from a file. Here's the Flowgraph and here is a screenshot of the results. The results show the four constellation points, and the data from the file source matches up perfectly with the data having gone though the entire transmit+receive chain. In the simulation I have a throttle block and a channel model block where the LimeSDR Source and LimeSDR Sink block would be. So far so good (at least as far as I can tell).
When I actually start transmitting this signal with the SDR, the received data no longer matches up with what is transmitted. Here's the flowgraph I've been using for the transmission. I added a protocol formatter and some FEC blocks that I could have removed for this illustration, but the point is that simply looking at what bits are going into the modulator vs what's being recovered, the two do not match up. The constellation looks good (as far as I can tell) but the bits are all wrong. Here's a screenshot showing the bits being transmitted. You'll notice in the screenshot of the transmitted signal that the signal has a repeating series of three flat top "1's" surrounded on both sides by a period of "0's" (at time 1.5ms and 3.5ms). This is a screenshot of the received bits. At time 1ms and 3ms you can see how it is has significantly more transitions between 1 and 0 than it should.
So at this point I'm stumped. The simulation worked but the real world test does not. I've messed around with the RRC filter properties a significant amount. I have no clue if the values I have chosen are correct as I have not found a tutorial or explanation on how to do so. I just looked at some of the example flowgraphs and made some guesses as to how those values were derived and applied those guesses to my use case. It worked well in the simulation so I thought it would be fine in the real world test. I've tried a variety of samples per symbol but my goal is for a 4800 bit per second transfer speed, and using different samples per symbol didn't help anyway. What should I change in order to get this to work?
Bonus question: The constellation object has QPSK and DQPSK, and the constellation modulator has a differential checkbox. What is the best practice combination of selections to get a differential QPSK modulation?
Related
having read this article about a guy who uses tensorflow to sort cucumber into nine different classes I was wondering if this type of process could be applied to a large number of classes. My idea would be to use it to identify Lego parts.
At the moment, a site like Bricklink describes more than 40,000 different parts so it would be a bit different than the cucumber example but I am wondering if it sounds suitable. There is no easy way to get hundreds of pictures for each part but does the following process sound feasible :
take pictures of a part ;
try to identify the part using tensorflow ;
if it does not identify the correct part, take more pictures and feed the neural network with them ;
go on with the next part.
That way, each time we encounter a new piece we "teach" the network its reference so that it can better be recognized the next time. Like that and after hundreds of iterations monitored by a human, could we imagine tensorflow to be able to recognize the parts? At least the most common ones?
My question might sound stupid but I am not into neural networks so any advice is welcome. At the moment I have not found any way to identify a lego part based on pictures and this "cucumber example" sounds promising so I am looking for some feedback.
Thanks.
You can read about the work of Jacques Mattheij, he actually uses a customized version of Xception1 running on https://keras.io/.
The introduction is Sorting 2 Metric Tons of Lego.
In Sorting 2 Tons of Lego, The software Side you can read:
The hard challenge to deal with next was to get a training set large
enough to make working with 1000+ classes possible. At first this
seemed like an insurmountable problem. I could not figure out how to
make enough images and to label them by hand in acceptable time, even
the most optimistic calculations had me working for 6 months or longer
full-time in order to make a data set that would allow the machine to
work with many classes of parts rather than just a couple.
In the end the solution was staring me in the face for at least a week
before I finally clued in: it doesn’t matter. All that matters is that
the machine labels its own images most of the time and then all I need
to do is correct its mistakes. As it gets better there will be fewer
mistakes. This very rapidly expanded the number of training images.
The first day I managed to hand-label about 500 parts. The next day
the machine added 2000 more, with about half of those labeled wrong.
The resulting 2500 parts where the basis for the next round of
training 3 days later, which resulted in 4000 more parts, 90% of which
were labeled right! So I only had to correct some 400 parts, rinse,
repeat… So, by the end of two weeks there was a dataset of 20K images,
all labeled correctly.
This is far from enough, some classes are severely under-represented
so I need to increase the number of images for those, perhaps I’ll
just run a single batch consisting of nothing but those parts through
the machine. No need for corrections, they’ll all be labeled
identically.
A recent update is Sorting 2 Tons of Lego, Many Questions, Results.
1CHOLLET, François. Xception: Deep Learning with Depthwise Separable Convolutions. arXiv preprint arXiv:1610.02357, 2016.
I have started this using IBM Watson's Visual Recognition.
I had six different bricks to be recognized on the transport belt background.
I am actually thinking about tensorflow, since I can have it running locally.
The codelab : TensorFlow for Poets, describes almost exactly what you want to achieve,
For a demo of the Watson version:
https://www.ibm.com/developerworks/community/blogs/ibmandgoogle/entry/Lego_bricks_recognition_with_Watosn_lego_and_raspberry_pi?lang=en
I've been using oxyplot for a month now and I'm pretty happy with what it delivers. I'm getting data from an oscilloscope and, after a fast processing, I'm plotting it in real time to a graph.
However, if I compare my application CPU usage to the one provided by the oscilloscope manufacturer, I'm loading a lot more the CPU. Maybe they're using some gpu-based plotter, but I think I can reduce my CPU usage with some modifications.
I'm capturing 10.000 samples per second and adding it to a LineSeries. I'm not plotting all that data, I'm decimating it to a constant number of points, let's say 80 points for a 20 secs measure, so I have 4 points/sec while totally zoomed out and a bit more detail if I zoom in to a specific range.
With the aid of ReSharper, I've noticed that the application is calling a lot of times (I've 6 different plots) the IsValidPoint method (something like 400.000.000 times), which is taking a lot of time.
I think the problem is that, when I add new points to the series, it checks for every point if it is a valid point, instead of the added values only.
Also, it spends a lot of time in the MeasureText/DrawText method.
My question is: is there a way to override those methods and to adapt it to my needs? I'm adding 10.000 new values each second, but the first ones remain the same, so there's no need for re-validate them. Also, the text shown doesn't change.
Thank you in advance for any advice you can give me. Have a good day!
I'm using a HackRF One device and its corresponding osmocom Sink block inside of gnuradio-companion. Because the input to this block is Complex (i.e. a pair of Floats), I could conceivably send it an enormously large value. At some point the osmocom Sink will hit a maximum value and stop driving the attached HackRF to output stronger signals.
I'm trying to figure out what that maximum value is.
I've looked through the documentation at a number of different sites, for both the HackRF One and the osmocom source and can't find an answer. I tried looking through the source code itself, but couldn't see any clear indication there, although I may have missed something there.
http://sdr.osmocom.org/trac/wiki/GrOsmoSDR
https://github.com/osmocom/gr-osmosdr
I also thought of deriving the value empirically, but didn't trust my equipment to get a precise measure of when the block started to hit the rails.
Any ideas?
Thanks
Friedman
I'm using a HackRF One device and its corresponding osmocom Sink block inside of gnuradio-companion. Because the input to this block is Complex (i.e. a pair of Floats), I could conceivably send it an enormously large value.
No, the complexes z must meet
because the osmocom sink/the underlying drivers and devices map that -1 – +1 range to the range of the I and Q DAC values.
You're right, though, it's hard to measure empirically, because typically, the output amplifiers go into nonlinearity close to the maximum DAC outputs, and on top of that, everything is frequency-dependent, so e.g. 0.5+j0.5 at 400 MHz doesn't necessarily produce the same electrical field strength as 0.5+j0.5 at 1GHz.
That's true for all non-calibrated SDR devices (which, aside from your typical multi-10k-Dollar Signal Generator, is everything, unless you calibrate for all frequencies of interest yourself).
I really like visualVM and think it's a great tool. However, after running for about an hour the graphs (cpu, mem, and others) start jumping around and requires a restart. I suspect this has something to do with the app trying to sample the dataset because there is too much data to show on the graph.
I've searched the issues list and don't see this listed. Given that's it's behaved like this for as long as I've used it and that others are complaining about it, I'm wondering if it's intended behavior. I guess that's the first question.
The second would be, why is it keeping all the data points, why not throw the oldest point away when a new point arrives and the buffer is full?
For the first question see this: http://java.net/projects/visualvm/lists/dev/archive/2011-02/message/7.
For second question: VisualVM does not keep all the data points, it throws the oldest point away when a new point arrives and the buffer is full. How did you came to the conclusion, that keeps all data.
what is the basic idea behind steganography?ie ,how do you get the hidden information?
suppose if it is an image and some text is within that image...how do you get that text?..
Every stenography algorithm is different in that respect. Every algorithm hides the information differently and thus getting the information back is different.
A simple example goes like this - Each pixel of the image is composed of 3 bytes, one for red, green and blue. Most people can't detect a difference of one bit in the color in an image so one option is to use the least significant bit of each color channel for your data. This way you can store 3 bits of information in every pixel with very little effect on the general quality of the image.
To get the information back you'll need to read the first bit of every color channel of every pixel and gather all the bits together.
This is just a very simple and almost trivial way to do stenography. Real stenography algorithms are somewhat more involved. Like in cryptography, there is no way to generically "unhide" all stenography. you need to know which algorithm you're trying to decode.
The very basic idea is that images contain tons of redundant information that your eye cannot see. For instance if you changed the last bit on each pixel there would be no visible change as almost all of the information about the color is the other bits. So you can encode messages using the last bit (the most basic algorithm). The histogram however will be changed and a large message will easily be detectable. As far a decoding the message itself, well, the message itself is probably using public key encryption so you will never know what the actual payload was.
Steganography unlike cryptography is considered broken if Eve (who is eavesdropping and practising steganalysis) knows that there is a message at all. The assumptions are based on that Alice and Bob are being watched and any communication is sign that they are up to something (aka prisoners, restrictive governments, all governments in the future hehe ;-))
And of course the algorithms become much more complex that just flipping the last bits, but encoding data that will not affect the structure of image (and become vulnerable to statistical attacks.) :
I read this book last summer and I thought is was an excellent introduction (it has a lot a psuedocode of the algorithms used)
http://www.amazon.com/Steganography-Digital-Media-Principles-Applications/dp/0521190193
Steganography, coming from greek Steganos(i'm greek :P) is the art of hiding messages. While cryptography is about scrambling a message, steganography is about a person not being able to locate the message.
There are many tools that do this procedure for you. Writing a tool like that can be a complicated procedure i think, though i haven't tried to do that. You would need to create a sophisticated approach of correctly using unused or seemingly not important image pixels or data, in order to add your own message, file etc. For some more information, please take a look at : http://www.symantec.com/connect/articles/steganography-revealed