Modulation classification via demodulation confidence? I'm not sure if this is the right place to post this question, but will try anyway :-) 

I recently started reading up on the field of automated modulation classification (AMC) where an algorithm tried to classify which modulation scheme an RF signal is using (eg BPSK, QPSK, etc..). Some if the common approaches include higher order statistics, deep neural networks, etc...

My question is, at least for digital modulation schemes with constellation diagrams, why cant this problem be solved by a very simple solution: try decoding the signal using various modulation schemes and see which gives you the most confidence. Confidence can be measured by something like mean distance to the closest constellation point of that scheme. 

I realize that this may not be the fastest solution to the problem, and it cannot easily be applied to analog schemes (e.g. FM), but would it at least work? What would be its biggest issues?

Thanks

(PS: my background in not anywhere close to digital communications, so forgive any ignorance)
try decoding the signal using various modulation schemes and see which gives you the most confidence


well, simply because your "confidence" measure is basically equivalently hard to design generally enough as the other methods you mention.

Also, the search space is simply too humongous. How would you decode all possible combinations of constellations, symbol rates, with unknown phase and timing offsets, over all possible combinations with multi-carrier systems without any prior attempt to narrow things down? How low would your detection thresholds have to be so you could classify even without having done system-specific synchronization (which you can't do, without first assuming a system)?