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hard decision-soft decision decoding

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Sep 29, 2003
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hard decision decoding

can somebody please give me a detailed explain that:
what is soft decision and hard decision decoding?and the diffrence between them.
thanks in adv.

soft decision decoding


you can look at this book:
"Error Control Coding; fundamentals and applications" by SHU LIN


hard decision soft decision

hard decision is for binary information.
but soft decision uses multi-bits information.

hard and soft decision decoding

hard decision is appropriate for BSC and uses hamming metric for decision.before using this metric,recived signal must convert to binary form (0,1).
soft decision can be used for about any channel and it uses eucliden metric for recived singnal is used as it is.

soft decision decoder

mehtesham gives the close answer and you can find a brief discussion of soft/hard decoding at Proakis/Salihi s' "communication system engineering".

In short, the difference is hamming / euclidean distance in hard / soft decoding.

hard decision coding

Hi guys,

For maximum likelihood detection, how do we go about to decide which one is the best to apply?



soft decision

Hey Guys,

I want you to look at it this way, the decoder allocated after the de-modulator and the channel and it recieves the transmitted voltages over the system, ofcourse due to noise and other factors the values of these voltages are varied some are severely and some not.
Hard decision almost goes after polarity like if your code is 1/3 repetition code( every bit becomes three bits ie. 0 becomes 000 and 1 becomes 111) and the 000 is sampled by -1,-1,-1 volts and the 111 bits fore +1,+1,+1 volts and sent over the channel, if the recieved voltage is -0.1,-0.1,1.5 then the decoder using Hard decision will take it as a 0 because the number of -ve voltages are greater than the positive. but what the soft decision decoder is that it sums them up so the overall voltage is +1.3 and that is more close to +3 volts of the 111 than the -3 volts of the 000.
AND Both uses Maximum Likelihood decision making, but in hard decision the decoder treats every bit ( of the three repeated bits) as an independant indetity without taking any info from the de-modulator about the other two bits, and thats not the case in Soft Decision

ofcourse Soft decision is more developed and provide better performance but its also more cost. so its a debate and you have to choose between cost and performance.

Thanks for you time.
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soft decision and hard decision

Can I say that the HArd Decision is used when a single radio is used and the soft decision is needed when cooperative users are available in a communication system
Please help

hard decoding


HOW Maximum Likelihood detector take its decision??????????????????

I am modeling DVB-S2 in matlab using toolbox functions
for ldpc decoding when i use soft decision in demodulator the ldpc encoder out put is invalid but when using hard decision demodulator its ok
can any body tell me why?

Hard decision decoding takes a stream of bits say from the 'threshold detector' stage of a receiver, where each bit is considered definitely one or zero. Eg. for binary signaling, received pulses are sampled and the resulting voltages are compared with a single threshold. If a voltage is greater than the threshold it is considered to be definitely a 'one' say regardless of how close it is to the threshold. If its less, its definitely zero.
Soft decision decoding requires a stream of 'soft bits' where we get not only the 1 or 0 decision but also an indication of how certain we are that the decision is correct.
One way of implementing this would be to make the threshold detector generate instead of 0 or 1, say:
000 (definitely 0), 001 (probably 0), 010 (maybe 0), 011 (guess 0),
100 (guess 1), 101 (maybe 1), 110 (probably 1) , 111(definitely 1).
We may call the last two bits 'confidence' bits.
This is easy to do with eight voltage thresholds rather than one.
This helps when we anticipate errors and have some 'forward error correction' coding built into the transmission. Define FEC precisely.

Example: A receiver receives a bit stream consisting of sequences of 8 bit words which contain 7 information bits and one parity bit. The parity bit is set at the receiver in such a way that the total number of ones in each 8 bit word is even. Even parity.
A soft decision threshold detector as described above generates the following outputs.

(i) 000 110 010 111 001 011 110 111
(ii) 000 110 010 111 001 011 110 001

What is the most likely 8-bit word in each case?

Say what convolutional coding is and a half rate coder abd 3/4.

The Viterbi alg can take these 'soft bit' words and compute distances etc. as easily as it deals with hard bits. No great additional complexity apart from dealing with words (in this example 3-bit words) rather than one bit words. But the decisions are likely to be much much better with the greater reliability being placed on bits we are certain about than on but we are more uncertain about.

Note: I found this answer from one of the websites.

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