The secrets of DSP

Almost every modern transceiver offers it: DSP, Digital Signal Processing. For a long time, I wondered if DSP wasn’t an overrated feature. In the end I decided that DSP is cool indeed, but also that it doesn’t do miracles. I found an interesting article from SGC about this technology (link) and decided to share some of it with you.

If we strip away the ‘Digital’ from Digital Signal Processing, we are left with something that we’ve been doing in electronics since it was first invented, signal processing. Signal processing is all about taking a signal, applying some change to it, and then getting a new signal out. That change might be amplification, filtering or something else, but nearly all electronic circuits can be considered to be signal processors.

Looked on in this way, the signal processor as a black box might be composed of discrete components like capacitors and resistors, or it could be a complex integrated circuit with many circuits to accomplish a more complex task, or it could be a digital system which accepts a signal on its input and outputs the changed signal. As long as it accomplishes its defined task, it doesn’t matter how the box works internally.

Digital systems don’t work with continuous waveforms. Much work was done trying to create analog computers to handle calculations on continuous systems, but analog computers proved to be inflexible, slow, and hard to reconfigure to new tasks. In particular, it was hard to implement general algorithms on them. Maybe if digital systems had not developed so fast through the 1950s and 1960s, we might have solved the problems, but by the 1960s, it was already rare to find an analog computer anywhere. Serious work was done on digital computers where complex algorithms could be coded relatively easily. This meant that we had to get our data into digital form, which is done by a A/D converter.

Once in the computer, the process could be reversed by playing it out through a D/A converter to produce a close approximation of the original waveform. Notice the words ‘close approximation’. No digital sampling system can perfectly reproduce the original signal because each sample is a single number representing the signal in some small, but finite interval. Modern techniques make it possible for that digital sample to be so good that you can’t tell the difference on your CD or DVD, but the difference is still there. Digital systems have errors, just like any system.

Once the signal exists inside our digital system as a stream of samples, we can now process them in a variety of ways. This is where the math gets complicated and we have a real need to know about the mathematics. However, if what needs to be done is simple enough so that it can be done with existing DSP chips, we may not need to know any of the complex mathematics ourselves, leaving it to the chip designers to make the math work right.

One of the biggest problems early developers encountered was the lack of processor power. Analog signal processors work in real time, DSP knows three stages: A/D conversion, processing and D/A conversion. If the electronics aren’t fast enough, you won’t be happy. The latest breed of DSP processors however are so fast, that you won’t notice any delays.

DSP benefits
DSP allows us to recognize a signal in noise by its characteristics, something analog filters couldn’t do. We can process out much of the noise, improving the ratio of signal to noise thereby making it more understandable. We can recognize interfering tones and process them out. Even more, we can adapt as the signal and the noise change over time. No algorithm is perfect, but compared to 20 years ago, the level of improvement in noise reduction is phenomenal. These advances makes digital noise reduction a reality for a wide variety of transceivers and receivers, allowing you to concentrate on the communication and not the noise.

If you want to know more about DSP, I recommend downloading this PDF file.

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