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    What is the difference between convolution coding and error correction coding?

    What is convolution coding. Why it is so important in digital communication. What is difference betwen convolution coding and error correction coding.

    •   Alt16th June 2007, 18:25

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    covolution coding

    Convolutional codes are widely used to encode digital data before transmission through noisy or error-prone channels. During encoding, k input bits are mapped to n output bits to give a rate k/n coded bitstream. The encoder consists of a shift register of kL stages, where L is described as the constraint length of the code.

    a convolutional code is a type of error-correcting code



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    convolution coding tutorial

    It is called convolution coding because it appears as though you convolve an impulse response with the input bit sequence... its because you perform modulo 2 addition on the contents of the shift register and give them in the output...
    There are various types in such convolution coding...

    systematic--where the input sequence is a part of the output sequence

    non-systematic--where the input sequence is not a part of the output sequence

    recursive--where the output of one of the modulo 2 adders is fed back to the input of the adder itself... such that it have infinite impulse response...

    non-recursive--where there is no feedback... such that it have finite impulse response...


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    •   Alt17th June 2007, 08:05

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    shift register convolution

    Convolution coding is error corection coding. I am agree with this but the what you have explain is called hamming code most probably. Would you give me specific defination of this ( convolution coding)



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    one sided noise density

    As u r performing modulo 2 addition , it is called convolution coding and the output parity bits depends on the no of message bits equal to constraint length...



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    recursive convolutional code and constraint

    Compared to linear block codes where we consider in terms of blocks of data will be send through the channel but here we can process inputs as such as they arrive. here it has the memory so that the output does not depend not only on the present input but also on the previous inputs..


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    modulo-2 convolutions

    Convolutional encoding with Viterbi decoding is a FEC technique that is particularly suited to a channel in which the transmitted signal is corrupted mainly by additive white gaussian noise (AWGN). You can think of AWGN as noise whose voltage distribution over time has characteristics that can be described using a Gaussian, or normal, statistical distribution, i.e. a bell curve. This voltage distribution has zero mean and a standard deviation that is a function of the signal-to-noise ratio (SNR) of the received signal. Let's assume for the moment that the received signal level is fixed. Then if the SNR is high, the standard deviation of the noise is small, and vice-versa. In digital communications, SNR is usually measured in terms of Eb/N0, which stands for energy per bit divided by the one-sided noise density.

    For more details, check this link:

    http://home.netcom.com/~chip.f/viter....html#specapps

    Ahmed



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    Re: Convolution coding

    convolutional coding is a form of error correction coding. the convolutional encoder can be considered as a shift register with desintaed outputs used to take out the encoded data. the decoding operation can be done by Viterbi algorithm.



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