The liberal use of AI generated images really cheapens the entire article. Please don't do it. At that point I suspect most of the text is also AI generated.
Only two images are AI generated where horses as carriers needed to be shown. Can you please explain why this is a problem? Thank you (Also, all text is written by me :)
I guess I just don't like the style of the images, they just scream "AI slop ahead!". Also I don't think they add anything of value to your article, which is indeed well written.
So kudos from someone working on radar signal processing!
This reads like someone proficient in signal processing is explaining the core concepts to another person who is already proficient in signal processing.
Exactly right! As somebody who’s spent a great deal of time with the discrete Fourier transform, I thought, “this article reads like it was written specifically for me.” I/Q modulation is new to me though.
Pro tip: If you're writing an article on the significance of something called I/Q, it's cool to somewhere in the first couple pages say something about what I/Q is.
I prefer a more "physical" explanation - you have two carriers: sin(wt) and cos(wt), and you're modulating bits I and Q onto the two carriers and adding them up before transmitting. Now, mathematically, that's the same as representing the two bits as I+jQ and multiplying it with cos(wt)+jsin(wt). Demodulation is simply multiplying that output with the complex conjugate cos(wt)-jsin(wt), which in physical terms translates to mixing with a local oscillator output and low pass filtering.
My go-to for I/Q is: Having two allows you to represent negative frequencies. With a normal, real signal, this is of course impossible (negative frequencies will automatically mirror the positive ones), but if you have a signal centered around e.g. 1 MHz, there's room for above-1MHz and below-1MHz to be meaningfully different. And _that_ allows you to get a complex signal (I/Q), once you pull the center down to 0 Hz for convenience of calculation.
Most technical writing is going to assume some familiarity with the discipline. If a reader encounters unfamiliar vocabulary in a technical article, they'd be well advised to look it up.
Yikes - why even mention the E and B fields? They aren't relevant to the rest of the article.
A few hours playing with Sine and Cosine generators in GNU radio can take you from book knowledge of I/Q complex signals into fully grokking it. You don't even need a radio, just your existing audio I/O.
I mentioned E and B fields so that the reader knows why we focus exclusively on sinusoids. Plus, linking the sinusoid to something we see in physics makes it more real.
There is a source block for your mic and or audio in. That was one of the first things I played with to understand sdr. I remember seeing a strong tone on a waterfall plot that I could not hear, thinking it was an articfact, then looking at the frequency and realizing I wouldn't be able to hear it. Turned out it was a crt TV. That kind of dates the story. Fun to be had.
Are there any other high-quality sources for articles about signal processing and its actual application in hardware/software?
I've taken signal processing classes at my college and while I have a good grasp of the theory I struggle with actual use case ideas, beyond implementing a simple fir filter on a stm32.
Some variation of QAM will always be used in communication. As soon as you deal in with EM-waves, be it physics, engineering or even biomedical stuff you will have to deal with complex numbers, which by extension is dealing with I/Q signals. You probably don't need this for programming a server or a website, but it's indispensable for signal processing.
Not just RF, also optical communications. Really, the only domain left where PAM transmission is used is baseband communication for electronics, and datacom for optics.
The liberal use of AI generated images really cheapens the entire article. Please don't do it. At that point I suspect most of the text is also AI generated.
Only two images are AI generated where horses as carriers needed to be shown. Can you please explain why this is a problem? Thank you (Also, all text is written by me :)
Safe to say that 150 years ago, his great-great-grandpa was ranting about photography putting painters out of work.
I guess I just don't like the style of the images, they just scream "AI slop ahead!". Also I don't think they add anything of value to your article, which is indeed well written.
So kudos from someone working on radar signal processing!
This reads like someone proficient in signal processing is explaining the core concepts to another person who is already proficient in signal processing.
Exactly right! As somebody who’s spent a great deal of time with the discrete Fourier transform, I thought, “this article reads like it was written specifically for me.” I/Q modulation is new to me though.
Pro tip: If you're writing an article on the significance of something called I/Q, it's cool to somewhere in the first couple pages say something about what I/Q is.
Q=Quadrature, I=In-phase
(As you point out not in the first couple pages, but waaay down)
he "explains" those
https://wirelesspi.com/two-birds-with-one-tone-i-q-signals-a...
Not trying to be charitable like furgot ... The wikipedia page is the first time I've seen authors go pro on the topic
https://www.pe0sat.vgnet.nl/sdr/iq-data-explained/
This is an excellent introduction to the concept and also to the why complex numbers are used to represent signal samples.
I prefer a more "physical" explanation - you have two carriers: sin(wt) and cos(wt), and you're modulating bits I and Q onto the two carriers and adding them up before transmitting. Now, mathematically, that's the same as representing the two bits as I+jQ and multiplying it with cos(wt)+jsin(wt). Demodulation is simply multiplying that output with the complex conjugate cos(wt)-jsin(wt), which in physical terms translates to mixing with a local oscillator output and low pass filtering.
Why would you want two carriers?
Twice as much information.
My go-to for I/Q is: Having two allows you to represent negative frequencies. With a normal, real signal, this is of course impossible (negative frequencies will automatically mirror the positive ones), but if you have a signal centered around e.g. 1 MHz, there's room for above-1MHz and below-1MHz to be meaningfully different. And _that_ allows you to get a complex signal (I/Q), once you pull the center down to 0 Hz for convenience of calculation.
Thank you for the suggestion. That's the point. I/Q introduced early gets too complicated. This foundation needs to be built up.
Only people with a low I/Q would misunderstand this notation!
Most technical writing is going to assume some familiarity with the discipline. If a reader encounters unfamiliar vocabulary in a technical article, they'd be well advised to look it up.
https://en.wikipedia.org/wiki/In-phase_and_quadrature_compon...
Yikes - why even mention the E and B fields? They aren't relevant to the rest of the article.
A few hours playing with Sine and Cosine generators in GNU radio can take you from book knowledge of I/Q complex signals into fully grokking it. You don't even need a radio, just your existing audio I/O.
I mentioned E and B fields so that the reader knows why we focus exclusively on sinusoids. Plus, linking the sinusoid to something we see in physics makes it more real.
> existing audio I/O
I never knew there even is such a thing. Where can I find it?
There is a source block for your mic and or audio in. That was one of the first things I played with to understand sdr. I remember seeing a strong tone on a waterfall plot that I could not hear, thinking it was an articfact, then looking at the frequency and realizing I wouldn't be able to hear it. Turned out it was a crt TV. That kind of dates the story. Fun to be had.
Dang, I just realized that I misread it. I was seeing "I/Q" where it says "I/O". My bad.
Are there any other high-quality sources for articles about signal processing and its actual application in hardware/software? I've taken signal processing classes at my college and while I have a good grasp of the theory I struggle with actual use case ideas, beyond implementing a simple fir filter on a stm32.
Great Scott Gadgets has an excellent series of videos on the subject.
https://www.greatscottgadgets.com/sdr/
Yet another thing from school I've never used in the software world.
By the way, QAM is (still) used in 4G and 5G.
Come be a DSP engineer. I take FFTs of IQ data almost every single day
Some variation of QAM will always be used in communication. As soon as you deal in with EM-waves, be it physics, engineering or even biomedical stuff you will have to deal with complex numbers, which by extension is dealing with I/Q signals. You probably don't need this for programming a server or a website, but it's indispensable for signal processing.
Work on low-level software for communications, especially RF, and you will see plenty of this stuff.
Not just RF, also optical communications. Really, the only domain left where PAM transmission is used is baseband communication for electronics, and datacom for optics.