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I am trying to find the answer to , what types of demodulation methods are exists. Each of my searches results with different names, but converging to one metric , which is finding the closest symbol among all the constellation points (square qams). In one reference it is called slicing , in another it is called "hard-decision", another one is named maximum likelihood...

Are all really the same ? is there any "soft-decision" metric ?

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  • \$\begingroup\$ In this context what is you distinction between soft and hard? \$\endgroup\$ – PlasmaHH Jan 12 '16 at 12:09
  • \$\begingroup\$ It's a good question, I searched for soft demodulation without any informative results... so I don't know if this term exists for QAM demodulation. \$\endgroup\$ – UdiW Jan 12 '16 at 12:35
  • \$\begingroup\$ It is kinda hard to answer if you don't really know what you are asking for... \$\endgroup\$ – PlasmaHH Jan 12 '16 at 12:41
  • \$\begingroup\$ Before considering demodulation methods, have you understood that you need to coherently produce a local oscillator. I mention this because without a phase locked (aka coherent) local oscillator demod of any type isn't going to work and, in fact the act of demodulation feeds back to the local oscillator to keep it nudged into coherency. \$\endgroup\$ – Andy aka Jan 12 '16 at 12:52
  • \$\begingroup\$ If you are meaning to soft-decoding , it's not what i'm looking for. As I wrote the three types yields the same metric for finding the minimum distance. So I can figure that in this case hard-decision is the same as maximum likelihood demodulation & slicing demodulation ? and I am thinking that the distinction between soft and hard if it is exists , this should be written anywhere... \$\endgroup\$ – UdiW Jan 12 '16 at 12:56
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There are techniques that use soft or hard decisions.

The most usual is a hard decision, where some sort of circuit guesses from that symbol alone which constellation point is closest, and outputs that one.

The soft decision output is where the circuit, instead of stating that X symbol is the most likely result, states that the received symbol is x distance away from X symbol.

The soft decisions have use further downstream, they allow error detection/correction circuits to know which symbols were reliable, and which were marginal. A sufficiently sophisticated error correcter would weight reliable symbols more strongly than dodgy ones, and so gain a small performance improvement over those that worked with only hard decisions.

The performance gain is small, and needs a more complicated error corrector, which is why both hard and soft decision systems are in use.

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  • \$\begingroup\$ O.k , if I understood you correctly soft decision is relevant if there is an error detection/correction ? but if what i'm considered is only the detection of the constellations points then the usual hard-decision/ML/slicer which are basically the same, is relevant techniques which are the most usual ? \$\endgroup\$ – UdiW Jan 12 '16 at 14:59

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