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Table Of Contents

MT Convolutional DeInterleave (MT Convolutional DeInterleaver (Standard)) (G Dataflow)

Version:
    Last Modified: February 7, 2018

    Performs the deinterleaving process using a fixed number of branches and fixed unit delay.

    A convolutional deinterleaver is the inverse of a convolutional interleaver. In convolutional deinterleaving, data elements pass cyclically through a set of branches. That is, in an N branch convolutional deinterleaver, the element 0 goes through branch 0, element 1 goes through branch 1, element N-1 goes through branch N-1, element N goes through branch 0, and so on. Each branch has different delays associated with it. Hence the data sent to each deinterleaver branch is delayed by a specific amount (the amount of delay in that particular branch) before the deinterleaver returns the data. In a convolutional interleaver, if the delay in branch number n is dn, maximum delay is max_delay and the minimum delay is min_delay, then for the corresponding convolutional deinterleaver, the delay in branch number n is: Dn = (max_delay+min_delay)-dn.

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    data in

    The input data to the deinterleaver.

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    number of branches

    The number of branches of the convolutional deinterleaver. Data elements pass through the branches in a cyclic fashion. For example, in an N branch convolutional deinterleaver, data element 0 goes through branch 0, element 1 goes through branch 1, element N-1 goes through branch N-1, element N returns through branch 0, and so on. Each branch incorporates different delays.

    Default: 0

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    unit delay

    The unit delay value. If this value is defined as D, then the number of delays on the ith branch is (i×D). If the total number of branches is N, then i = 0, 1,…, N-1.

    Default: 0

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    initial state

    The shift register values when the convolutional deinterleaver begins operation.

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    error in

    Error conditions that occur before this node runs.

    The node responds to this input according to standard error behavior.

    Standard Error Behavior

    Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

    error in does not contain an error error in contains an error
    If no error occurred before the node runs, the node begins execution normally.

    If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

    If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

    Default: No error

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    reset?

    A Boolean that determines whether to check the current input parameters. The current input parameters are always checked on the first run of this node.

    TRUE Checks input parameters.
    FALSE Does not check input parameters.

    Default: TRUE

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    data out

    The output of the convolutional deinterleaver.

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    error out

    Error information.

    The node produces this output according to standard error behavior.

    Standard Error Behavior

    Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

    error in does not contain an error error in contains an error
    If no error occurred before the node runs, the node begins execution normally.

    If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

    If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

    Examples of Convolutional Interleaving and Deinterleaving

    The following example demonstrates convolutional interleaving and deinterleaving. Let the data in be: x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, x10, x11, x12, x13, …

    Interleaver Input Interleaver Output

    D = unit delay in the path.

    Assume for this example that the unit delay = 1, and the initial state shift registers are initialized with values of 0 for both the interleaver and the deinterleaver.

    Interleaved Data: x0, 0, 0, 0, x4, x1, 0, 0, x8, x5, x2, 0, x12, x9, …

    Deinterleaver Input Deinterleaver Output

    Deinterleaved Data: 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, …

    Where This Node Can Run:

    Desktop OS: Windows

    FPGA: Not supported

    Web Server: Not supported in VIs that run in a web application


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