Seminar on receiver noise and covariance detection

31.10.2014 19:35

Here are slides of yet another seminar I gave at the School a few weeks ago to an audience of one. Again, I'm also posting them here in case it might be useful beyond merely incrementing my credit point counter. Read below for a short summary or dive directly into the paper if it sounds like fun reading to you. It's only four pages this time - I was warned that nobody has time to read my papers.

Effects of non-Gaussian noise on covariance-based detectors title slide

Like all analog devices, radio receivers add some noise to the signal that is passing through them. Some of this noise is due to pretty basic laws of physics, like thermal noise or noise due to various quantum effects in semiconductors. Other sources of noise however come from purely engineering constraints. These are for example crosstalks between parts of the circuit, non-ideal filters and so on. When designing receivers, all these noise sources are usually considered equivalent, since in the end only total noise power is what matters. For instance, you might design a filter so that it filters out unwanted signals until their power is around thermal noise floor. It doesn't make sense to have more attenuation, since you won't see much improvement in total noise power.

However, when you are using a receiver as a spectrum sensor, very weak spurious signals buried in noise become significant. After all, the purpose of a spectrum sensor is exactly that: to detect very weak signals in presence of noise. Since you don't know what kind of signal you are detecting, a local oscillator harmonic might look exactly like valid transmission you want to detect. Modern spectrum sensing methods like covariance- and eigenvalue-based detectors work well in presence of white noise. Because of this it might be better for a receiver designer to trade low total noise power for noise with a higher power, but one that looks more like white noise.

The simulations I describe were actually motivated by the difference I saw between theoretical performance of such detectors and practical experiments with an USRP when preparing one of my earlier seminars. I had a suspicion that spurious signals and non-white noise from the USRP's front-end could be causing this. To see if it's true, I've created a simulation using Python and NumPy that checks the minimal detectable power for two detectors in presence of different spurious sine signals and noise, colored by digital down-conversion.

In the end, I found out that periodic spurious signals affected the minimal detectable signal power even when they were 30 dB below the thermal noise power, regardless of frequency. Similarly, digital down-conversion alone also affects detector performance because of correlation it introduces into thermal noise. However since oversampling ADC have so many other practical benefits, DDC is most likely a net gain even in a spectrum sensing application. On the other hand, periodic components in receiver noise should be avoided as far as possible.

Posted by Tomaž | Categories: Analog

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