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.
The input data to the deinterleaver.
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.
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.
The shift register values when the convolutional deinterleaver begins operation.
Error conditions that occur before this node runs.
The node responds to this input according to standard error behavior.
Default: no error
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.
||Checks input parameters.
||Does not check input parameters.
The output of the convolutional deinterleaver.