Hi Rich! HA! You've come to the *right* neighborhood!
There's actually more [tag:gnuradio] stuff on StackOverflow than I can keep check on: http://stackoverflow.com/questions/tagged/gnuradio A lot of mathematically more interesting questions happen on dsp.SE http://dsp.stackexchange.com/ and specifically http://dsp.stackexchange.com/questions/tagged/gnuradio I'd love if anyone could pick up on those – the DSP.SE community is really great at helping people understand and improve their own questions, so these Q/A pairs and discussions are often pretty nice! For example, Phil Frost has a question I've not found the time addressing yet. It'd be really nice if someone picked up that slack :D Talking of Phil: Then there's the amateur radio SE site, and that has very mixed-topic questions; many are very operation-centric, other would belong on dsp.SE, and yet other are discussion of basic Radio concept. I like the mix, but I clearly don't check these often, so if everyone could have a look every few months: http://ham.stackexchange.com Cheers, Marcus On 24.08.2016 00:36, Richard Bell wrote: > Great answer. I wish I could upvote it! There should be a GNU Radio > Stack Exchange type thing. > > Rich > > On Tue, Aug 23, 2016 at 3:07 PM, Andy Walls > <a...@silverblocksystems.net <mailto:a...@silverblocksystems.net>> wrote: > > On Tue, 2016-08-23 at 12:00 -0400, > discuss-gnuradio-requ...@gnu.org > <mailto:discuss-gnuradio-requ...@gnu.org> > wrote: > > Message: 7 > > Date: Mon, 22 Aug 2016 18:14:29 -0700 (MST) > > From: Paul Creaser <drpaulcrea...@gmail.com > <mailto:drpaulcrea...@gmail.com>> > > > > I've just started studying methods used to detect and then > filter out/remove > > cyclic noise from known signals. > > > > I have a signal of 256 samples which repeats itself. I take this > signal, > > attenuate it and add noise at a specific band (frequency band), > for example > > 50 Hz Sine Wave. In the simplest case this is none varying. > However in the > > future it will vary slowly over time. > > I'm not quite sure what you mean by "cyclic noise", but the > example you > give is 50 Hz (or 60 Hz) hum, so a narrowband interference. > > > > What I would like to do is find the power level of the additive > cyclic noise > > (, which should be the difference between the two signals) and > where in the > > frequency spectrum this noise exists. Using this information, I > would hope > > to use weighting to recover the original signal. > > If the noise is always out of the channel of your signal of interest, > then a bandpass filter will do the job and your done. > > If the noise is in the channel of your signal of interest, then it > sounds like what you really want in the end is an adaptive > equalizer or > filter. > > If you're not afraid of a lot of work: > Just dive into implementing a Least Mean Squares (LMS) adaptive > filter. > > You can either make it Data-Aided (DA), adapting the filter when it > detects and operates on a known preamble; or Decision Directed (DD), > adapting the filter every time it makes a decision about what a > data bit > should be. > > I prefer using a Data-Aided LMS adaptive filter, as I often work with > signals that have known preambles. > > Such a system would look something like: > > received samples source -> channel filter -> automatic gain control -> > correlator to detect and mark the preamble -> LMS DA adaptive filter > -> ... > > Translating that to example GNURadio blocks: > > USRP Source -> Freq Xlating FIR Filter -> Feed Forward AGC -> > Correlation Estimator -> (Your custom LMS DA filter block) -> ... > > > > *Steps* > > > > 1 I take the original and modified signal and rescale the > modified signal to > > match the original. > > > > At the moment I use a very naive approach which is to take the > absolute sum > > of the 256 samples for both signals and from this calculate a > simple scale > > factor. I think this should be OK where I have narrow band > noise, but it may > > fail badly in other cases where the noise levels are high. > > > > 2 Next I take the FFT of the two signals (256 samples). > > > > 3 Calculate the noise > > > > Using the difference between the FFTs, I then calculate the > noise power. > > > > *Two questions?* > > > > 1 The rescaling method is very basic, using absolute accumulated > sums. Does > > GNU radio have any blocks, which could perform this auto-scaling > more > > effectively? > > GNURadio has several AGC blocks. They all have their quirks. > Pick one > an try to make it work. > > > > 2 Using the basic difference between the FFT's, such as the absolute > > magnitude difference, should provide a starting point for > calculating the > > noise power. Again is this naive? > > Noise power and noise density have specific meanings which I don't > think > match what you're thinking about here. AFAICT, you want to know the > power of an in-channel narrowband interference (so that you can > ultimately filter it out). > > Looking at FFT's will give you a feel for the situation, but it's kind > of a blunt instrument, if you plan of filtering by direct FFT bin > scaling or excision. > > It really sounds like what you want is an adaptive equalizer (aka > adaptive filter). > > There's lots of existing literature on equalizers. > This lecture is still a little too advanced for most folks, but it has > the basic concepts covered clearer than most others I could find on > Google: > > http://www.eecg.toronto.edu/~johns/nobots/courses/ece1392/equalization2.pdf > > <http://www.eecg.toronto.edu/%7Ejohns/nobots/courses/ece1392/equalization2.pdf> > > > Section 14.6 of this book describes the LMS algorithm: > > https://www.amazon.com/Mathematical-Methods-Algorithms-Signal-Processing/dp/0201361868 > > <https://www.amazon.com/Mathematical-Methods-Algorithms-Signal-Processing/dp/0201361868> > > And here is a PDF copy I spotted on the internet (click at your own > risk): > > https://www.u-cursos.cl/usuario/834c0e46b93fd72fd8408c492af56f8d/mi_blog/r/4%29_Todd_Moon_Mathematical_Methods_and_Algorithms_for_Signal_Processing.pdf > > <https://www.u-cursos.cl/usuario/834c0e46b93fd72fd8408c492af56f8d/mi_blog/r/4%29_Todd_Moon_Mathematical_Methods_and_Algorithms_for_Signal_Processing.pdf> > > -Andy > > > > _______________________________________________ > Discuss-gnuradio mailing list > Discuss-gnuradio@gnu.org <mailto:Discuss-gnuradio@gnu.org> > https://lists.gnu.org/mailman/listinfo/discuss-gnuradio > <https://lists.gnu.org/mailman/listinfo/discuss-gnuradio> > > > > > _______________________________________________ > Discuss-gnuradio mailing list > Discuss-gnuradio@gnu.org > https://lists.gnu.org/mailman/listinfo/discuss-gnuradio
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