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# Random Integer Generator

Generate integers randomly distributed in range [0, M-1]

## Library

Random Data Sources sublibrary of Comm Sources

## Description

The Random Integer Generator block generates uniformly distributed random integers in the range [0, M-1], where M is the Set size defined in the dialog box.

The Set size can be either a scalar or a row vector. If it is a scalar, then all output random variables are independent and identically distributed (i.i.d.). If the Set size is a vector, then the length of the vector determines the number of output channels. The channels can have differing output ranges.

If the Initial seed parameter is a constant, then the resulting noise is repeatable.

### Attributes of Output Signal

The output signal can be a column or row vector, a two-dimensional matrix, or a scalar. The number of rows in the output signal corresponds to the number of samples in one frame and is determined by the Samples per frame parameter. The number of columns in the output signal corresponds to the number of channels and is determined by the number of elements in the Set size parameter. See Sources and Sinks in Communications System Toolbox™ User's Guide for more details.

## Parameters

Set size

The set size determines the range of output values. The block generates integers ranging from 0 to Set size – 1. Specify the set size as a scalar or row vector of positive integers. The number of elements in Set size correspond to the number of independent channels output from the block.

Source of initial seed

The source of the initial seed for the random number generator. Specify the source as either `Auto` or `Parameter`. When set to `Auto`, the block uses the global random number stream.

 Note:   When Source of initial seed is `Auto` in ```Code generation``` mode, the random number generator uses an initial seed of zero. Therefore, the block generates the same random numbers each time it is started. Use `Interpreted execution` to ensure that the model uses different initial seeds. If ```Interpreted execution``` is run in `Rapid accelerator` mode, then it behaves the same as `Code generation` mode.
Initial seed

The initial seed value for the random number generator. Specify the seed as a nonnegative integer scalar. Initial seed is available when the Source of initial seed parameter is set to `Parameter`.

Sample time

The time between each sample of a column of the output signal.

Samples per frame

The number of samples per frame in one channel of the output signal. Specify Samples per frame as a positive integer scalar.

 Note:   The time between output updates is equal to the product of Samples per frame and Sample time. For example, if Sample time and Samples per frame equal one, the block outputs an integer every second. If Samples per frame is increased to 10, then a 10-by-1 vector is output every 10 seconds. This ensures that the equivalent output rate is not dependent on the Samples per frame parameter.
Output data type

The output type of the block can be specified as a `boolean`, `uint8`, `uint16`, `uint32`, `single`, or `double`. The default is `double`. Single outputs may lead to different results when compared with double outputs for the same set of parameters. For Boolean typed outputs, the Set size must be `2`.

Simulate using

Select the simulation mode.

`Code generation`

On the first model run, simulate and generate code. If the structure of the block does not change, subsequent model runs do not regenerate the code.

If the simulation mode is `Code generation`, System objects corresponding to the blocks accept a maximum of nine inputs.

`Interpreted execution`

Simulate model without generating code. This option results in faster start times but can slow subsequent simulation performance.

## Examples

expand all

Open the QPSK model. The model generates QPSK data, applies white noise, and displays the resulting constellation diagram.

Run the model.

Change the Eb/No of the AWGN Channel block from 15 dB to 10 dB.

The noise level increases as shown by the greater distance between the samples.

## See Also

#### Introduced before R2006a

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