# MT Convolutional Encoder (Generator Matrix) (G Dataflow)

Generates an encoded bit stream based on a generator matrix that you set.

## input bit stream

Bit sequence representing the data bits to encode. Use the bits generated by MT Generate Bits to produce this bit stream or wire a custom data bit stream to this parameter.

## generator matrix

The generator connection polynomial matrix that sets the convolutional feedforward node connections in octal format.

The convolutional node is modeled as a linear feedforward shift register arrangement consisting of k rows with K-1 shift registers per row, where k denotes the data word length and K denotes the constraint length. If a ij {0 ≤ in-1, 0 ≤ jk-1} denotes a particular element in the generator matrix, the row index i corresponds to the convolutional node output y i that is affected by this element, while the column index j corresponds to the jth row in the k row shift register arrangement. Thus a ij specifies how the K bits in the jth row of the feedforward shift register matrix affects the ith output of the convolutional node.

For a rate of 2/3, the generator matrix is specified as follows:

$\left(\begin{array}{cc}100100& 011000\\ 011100& 101000\\ 110000& 010000\end{array}\right)=\left(\begin{array}{cc}44& 30\\ 34& 50\\ 60& 20\end{array}\right)$

The matrix on the right represents the elements in octal format. Zeros are padded at the end of the corresponding code generator sequences such that their total length is a multiple of three digits. The following diagram depicts the rate 2/3 convolutional node corresponding to the previously mentioned generator matrix, with a constraint length equal to 4. In the following diagram, D represents a shift register or memory element.

Here, y i j , 0 ≤ jn-1 denotes the jth output of this node, in the ith instance.

Default: $\left(\begin{array}{c}5\\ 7\end{array}\right)$

## constraint length

The maximum number of encoded bits that can be affected by a single input bit. This value represents (1 + maximal memory order), where maximal memory order refers to the length of the longest shift register chain in the convolutional encoder.

Default: 3

## initial state

The encoder initialization state for the k(K-1) shift registers, where k is the input data word length and K specifies the constraint length. On the first call to this node, and thereafter when you configure reset? to TRUE, the encoder state is reset to this value on each call to this node. When you configure reset? to FALSE, the final state from the previous iteration is used in subsequent calls to this node and LabVIEW ignores the initial state parameter.

Default: 0

## error in

Error conditions that occur before this node runs. The node responds to this input according to standard error behavior.

Default: no error

## reset?

A Boolean that determines whether the internal state of the encoder is cleared.

 TRUE Clears any buffered bits from previous iterations. Also initializes the encoder to start from the initial state parameter that you specify. FALSE Continues encoding from the previous iteration. Any buffered bits from the previous iteration are added to the beginning of the input bit stream prior to encoding.

Default: TRUE

## output bit stream

Convolutional-encoded code word returned by this node. Wire this parameter to MT Convolutional Decode to recover the input data stream.

## final state

The value for the k(K-1) shift registers as the right-aligned (least significant) k(K-1) bits when this node completes execution, where K is the constraint length and k is the data word length in bits.

## error out

Error information. The node produces this output according to standard error behavior.

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported