# comm.DPDCoefficientEstimator

Estimate memory-polynomial coefficients for digital predistortion

## Description

The `comm.DPDCoefficientEstimator`

System object™ estimates the coefficients of a memory polynomial for digital pre-distortion
(DPD) of a nonlinear power amplifier, given the baseband equivalent input and baseband
equivalent output of the power amplifier. For more information, see Digital Predistortion.

To compute predistortion coefficients:

Create the

`comm.DPDCoefficientEstimator`

object and set its properties.Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?

## Creation

### Description

creates a digital predistortion coefficient estimator System object to estimate the coefficients of a memory polynomial for digital
predistortion (DPD) of a nonlinear power amplifier.`estimator`

= comm.DPDCoefficientEstimator

sets properties using one or more name-value pairs. For example,
`estimator`

= comm.DPDCoefficientEstimator(`Name`

,`Value`

)```
comm.DPDCoefficientEstimator('PolynomialType','Cross-term memory
polynomial')
```

configures the predistortion coefficient estimator System object to estimate the coefficients for a memory-polynomial with cross terms.
Enclose each property name in quotes.

## Properties

## Usage

### Description

### Input Arguments

### Output Arguments

## Object Functions

To use an object function, specify the
System object as the first input argument. For
example, to release system resources of a System object named `obj`

, use
this syntax:

release(obj)

## Examples

## More About

## References

[1] Morgan, Dennis R., Zhengxiang Ma,
Jaehyeong Kim, Michael G. Zierdt, and John Pastalan. "A Generalized Memory Polynomial Model
for Digital Predistortion of Power Amplifiers." *IEEE ^{®} Transactions on Signal Processing*. Vol. 54, Number 10, October
2006, pp. 3852–3860.

[2] M. Schetzen. *The
Volterra and Wiener Theories of Nonlinear Systems.* New York: Wiley,
1980.

## Extended Capabilities

## Version History

**Introduced in R2019a**