System object: comm.gpu.AWGNChannel
Add white Gaussian noise to input signal
Y = step(H,X)
Y = step(H,X,VAR)
Y = step(H,X) adds white Gaussian noise to input X and returns the result in Y. The input X can be a double or single precision data type scalar, vector, or matrix with real or complex values. The dimensions of input X determine single or multichannel processing. For an M-by-N matrix input, M represents the number of time samples per channel and N represents the number of channels. M and N can be equal to 1. The object adds frames of length M of Gaussian noise to each of the N channels independently.
Y = step(H,X,VAR) uses input VAR as the variance of the white Gaussian noise. This applies when you set the NoiseMethod property to Variance and the VarianceSource property to Input port. Input VAR can be a positive scalar or row vector with a length equal to the number of channels. VAR must be of the same data type as input X.
Note: H specifies the System object™ on which to run this step method.
The object performs an initialization the first time the step method is executed. This initialization locks nontunable properties and input specifications, such as dimensions, complexity, and data type of the input data. If you change a nontunable property or an input specification, the System object issues an error. To change nontunable properties or inputs, you must first call the release method to unlock the object.