# Filter

**Libraries:**

RF Blockset /
Idealized Baseband

## Description

Use the Idealized Baseband Filter block to filter RF complex baseband signals in Simulink. You can use the Butterworth, Chebyshev, or inverse Chebyshev design methods to design your filter. You can also model your filter either in the time- or frequency-domain and plot the filter characteristics.

To design an RF filter with impedance mismatches, use the Circuit Envelope Filter block.

**Note**

The Idealized Baseband Filter block replaces the Lowpass RF Filter, Highpass RF Filter, Bandpass RF Filter, and Bandstop RF Filter blocks.

## Examples

## Ports

### Input

**Port_1** — Time-dependent input signal

real scalar | real column | complex scalar | complex column

Time-dependent input signal, specified as a real scalar, real column, complex scalar, or complex column. A column represents consecutive points in time.

**Data Types: **`double`

| `single`

### Output

**Port_1** — Time-dependent output signal

complex scalar | complex column

Time-dependent output signal, returned as a complex scalar or complex column. The output time-dependent signal is equal in size to the input time-dependent signal.

**Data Types: **`double`

| `single`

## Parameters

### Main

**Design method** — Filter design method

`Butterworth`

(default) | `Chebyshev`

| `Inverse Chebyshev`

Filter design method, specified as one of the following:

`Butterworth`

`Chebyshev`

`Inverse Chebyshev`

**Filter type** — Filter response type

`Lowpass`

(default) | `Highpass`

| `Bandpass`

| `Bandstop`

Filter response type, specified as one of the following:

`Lowpass`

— Simulates a lowpass filter type with the design specified in**Design method**.`Highpass`

— Simulates a highpass filter type with the design specified in**Design method**.`Bandpass`

— Simulates a bandpass filter type with the design specified in**Design method**.`Bandstop`

— Simulates a bandstop filter type with the design specified in**Design method**.

**Implement using filter order** — Implement using filter order

`off`

(default) | `on`

Select this parameter to implement the filter order manually.

**Filter order** — Filter order

`3`

(default) | integer greater than `2`

Filter order, specified as a integer greater than `2`

. If you
set** Filter design** to `Lowpass`

or
`Highpass`

, specify the number of lumped storage elements.
If you set ** Filter design** to `Bandpass`

or `Bandstop`

, specify twice the number of lumped storage
elements.

#### Dependencies

To enable this parameter, select **Implement using filter
order**.

**Passband frequency (Hz)** — Passband frequency

`1e9`

(default) | positive real scalar | positive ascending two-tuple vector

Passband frequency for lowpass, highpass, and bandpass filter types, specified as
a positive real scalar or positive ascending two-tuple vector in Hz. Based on the
**Filter Type**, accepted value types and default values differ as
follows.

Filter Type | Value Type | Default Values (Hz) |
---|---|---|

Lowpass | Positive real scalar | `1e9` |

Highpass | Positive real scalar | `2000000000` |

Bandpass | Positive ascending two-tuple vector | `[2000000000 3000000000]` |

#### Dependencies

To enable this parameter, set **Filter type** to
`Lowpass`

, `Highpass`

, or
`Bandpass`

.

**Passband attenuation (dB)** — Passband attenuation

`10*log10(2)`

(default) | positive real scalar

Passband attenuation of the filter, specified as a positive real scalar in dB. For bandpass filters, this value is applied equally to both edges of the passband.

#### Dependencies

To enable this parameter, set **Filter type** to
`Lowpass`

, `Highpass`

, or
`Bandpass`

.

**Stopband frequencies (Hz)** — Stopband frequencies for bandstop filters

`2000000000`

(default) | positive real scalar | positive ascending two-tuple vector

Stopband frequencies for bandstop filters, specified as either a positive real
scalar or positive ascending two-tuple vector in Hz. Based on the **Filter
Type** and **Implement using filter order** parameters,
accepted value types and default values differ as follows.

Filter Type | Value Type | Default Values (Hz) | To enable this parameter |
---|---|---|---|

Lowpass | Positive real scalar | `2000000000` | Set Filter type to
`Lowpass` and clear Implement using
filter order. |

Highpass | Positive real scalar | `1000000000` | Set Filter type to
`Highpass` and clear Implement using
filter order. |

Bandpass | Positive ascending two-tuple vector | `[1500000000 3500000000]` | Set Filter type to
`Bandpass` and clear Implement using
filter order. |

Bandstop | Positive ascending two-tuple vector | `[2100000000 2900000000]` | Set Filter type to
`Bandstop` and clear or select
Implement using filter order. |

**Stopband attenuation (dB)** — Stopband attenuation

`40`

(default) | positive real scalar

Stopband attenuation, specified as a positive real scalar greater than the
**Passband attenuation (dB)** value in dB.

#### Dependencies

To enable this parameter, you can either:

Set

**Filter type**to`Lowpass`

,`Highpass`

, or`Bandpass`

and clear**Implement using filter order**.Set

**Filter type**to`Bandstop`

, select**Implement using filter order**.

**Carrier frequency (Hz)** — Center of signal bandwidth

`1e9 Hz`

(default) | positive real scalar

Center of the signal bandwidth with respect to the filter transfer function, specified as a positive real scalar in Hz. The signal bandwidth is $$\frac{1}{\text{SimulinkStepSize}}$$.

**Simulate using** — Type of simulation to run

`Interpreted execution`

(default) | `Code generation`

Type of simulation to run, specified as one of the following:

`Interpreted execution`

— Simulate the model using the MATLAB^{®}interpreter. This option shortens the startup time, but the speed of the subsequent simulations is slower than when you use the`Code generation`

option. Use this mode to debug the source code of the block.`Code generation`

— Simulate the model using generated C code. The first time you run a simulation, Simulink^{®}generates C code for the block. The C code is reused for subsequent simulations as long as the model does not change. This option requires additional startup time, but the speed of the subsequent simulations is faster than when you use the`Interpreted execution`

option.

### Modeling

**Modeling domain** — Modeling domain

`Time domain (Fixed step)`

(default) | `Time domain (Continuous)`

| `Frequency domain (Digital filter)`

Modeling domain, specified as one of the following:

`Time domain (Fixed step)`

— Model using fixed-step solvers (`NDF2`

,`Trapezoidal`

, and`Backward Euler`

)`Time domain (Continuous)`

— Model using continuous or stiff solvers (`ode15s`

,`ode23s`

,`ode23t`

, and`ode23tb`

)`Frequency domain (Digital filter)`

— model using a 1-D digital filter.

**Solver** — Time-domain solvers

`NDF2`

(default) | `Trapezoidal`

| `Backward Euler`

| `ode15s`

| `ode23s`

| `ode23t (trap)`

| `ode23tb (trap+BE)`

Fixed-step and continuous time-domain solvers, specified as one of the following:

**Fixed-step Solvers**

`NDF2`

— Balance narrowband and wideband accuracy. This solver is suitable for situations where the frequency content of the signals in the system is unknown relative to the Nyquist rate.`Trapezoidal`

— Perform narrowband simulations. Frequency warping and the lack of damping effects make this method inappropriate for most wideband simulations.`Backward Euler`

— Simulate the largest class of systems and signals. Damping effects make this solver suitable for wideband simulation, but overall accuracy is low.

**Continuous Solvers**

`ode15s`

— Solve stiff differential equations and DAEs using a variable order method`ode23s`

— Solve stiff differential equations using a low-order method`ode23t (trap)`

— Solve moderately stiff ODEs and DAEs using a trapezoidal rule`ode23tb (trap+BE)`

— Solve stiff differential equations using a trapezoidal rule and backward differentiation formula

#### Dependencies

To enable:

Fixed-step time-domain solvers, set

**Modeling domain**to`Time domain (Fixed step)`

.Continuous time-domain solvers, set

**Modeling domain**to`Time domain (Continuous)`

.

**FIR filter length** — Filter length of 1-D digital filter

`128`

(default) | real positive integer

Filter length of the 1-D digital filter or impulse response duration, specified as a real positive integer.

#### Dependencies

To set this parameter, set **Modeling domain** to
`Frequency domain (Digital filter)`

.

### Visualization

**First plot type** — Plot type

`S21`

(default) | `Phase delay`

| `Group delay`

| `Impulse response`

| `Step response`

Plot type of the first plot, specified as one of the following:

`S21`

`Phase delay`

`Group delay`

`Impulse response`

`Step response`

**Impulse response arguments** — Input arguments to plot impulse response

`[ 1e-11, 1e4]`

(default) | two-element vector

Input arguments to plot the impulse response, specified as a two-element vector.
Plot the impulse response by specifying the sample time of the input signal and the
number of samples in this parameter. For more information, see `impulse`

.

#### Dependencies

To set this parameter, set **First plot type** or
**Second plot type** to ```
Impulse
response
```

.

**Step response arguments** — Input arguments to plot step response

`[ 1e-11, 1e4, 1e-10 ]`

(default) | three-element vector

Input arguments to plot the step response, specified as a three-element vector.
Plot the step response by specifying the sample time of the input signal, the number
of samples, and the amount of time required for the step signal to reach the maximum
value in this parameter. For more information, see `stepresp`

.

#### Dependencies

To set this parameter, set **First plot type** or
**Second plot type** to ```
Step
response
```

.

**First plot y-axis units** — Y-axis units of first plot

`Magnitude (dB)`

(default) | `Magnitude (linear)`

| `Angle (degrees)`

| `Real`

| `Imaginary`

Y-axis units of the first plot, specified as one of the following:

`Magnitude (dB)`

`Magnitude (linear)`

`Angle (degrees)`

`Real`

`Imaginary`

#### Dependencies

To set this parameter, set **First plot type** to
`S21`

.

**Second Plot type** — Plot type of second plot

`None`

(default) | `S21`

| `Phase delay`

| `Group delay`

| `Impulse response`

| `Step response`

Plot type of the second plot, specified as one of the following:

`None`

`S21`

`Phase delay`

`Group delay`

`Impulse response`

`Step response`

**Second plot y-axis units** — Y-axis units of second plot

`Magnitude (dB)`

(default) | `Magnitude (linear)`

| `Angle (degrees)`

| `Real`

| `Imaginary`

Y-axis units of the second plot, specified as one of the following:

`Magnitude (dB)`

`Magnitude (linear)`

`Angle (degrees)`

`Real`

`Imaginary`

#### Dependencies

To set this parameter, set **Second plot type** to
`S21`

.

**X-axis frequency points (Hz)** — Frequency points to plot S-parameter data

`logspace(8,10,2001)`

(default) | positive real vector

Frequency points to plot the S-parameter data, specified as a positive real vector in Hz.

**X-axis scale** — Linear or logarithmic X-axis scale

`Linear`

(default) | `Logarithmic`

Select this parameter to plot your data on a linear or logarithmic X-axis scale.
Specify `Linear`

or
`Logarithmic`

.

**Y-axis scale** — Linear or logarithmic Y-axis scale

`Linear`

(default) | `Logarithmic`

Select this parameter to plot your data in a linear or logarithmic Y-axis scale.
Specify `Linear`

or
`Logarithmic`

.

**Plot Sparameter characterstics** — Plot S-parameters data

button

Select this button to plot the characteristics of the S-parameters data.

## Algorithms

### Determine FIR Filter Coefficients

The software calculates the discrete FIR filter coefficients using the **Carrier frequency (Hz) **and **FIR filter length
** parameters and the transfer function specified using the derived filter poles
and zeros.

The following steps are followed to determine the **Discrete FIR
Filter** block direct form coefficients:

Determine the frequency points contained in the bandwidth centered around the carrier frequency using this formula.

$$\begin{array}{l}Freqs=\left[\left(\left(\frac{-ff{t}_{Len}}{2}\right):\left(\frac{ff{t}_{Len}}{2}-1\right)\right)\times \left(\frac{1}{{t}_{step}\times ff{t}_{Len}}\right)\right]+{f}_{carrier}\\ \text{where}\\ {f}_{carrier}-\text{CarrierfrequencyinHz}\\ ff{t}_{Len}-\text{FIRfilterlength}\\ {t}_{step}-\text{Timestepofthefilter}\end{array}$$

Use the

`rffilter`

object and its functions to determine the rational analog filter transfer function from the mask parameters in [z,p,k] form.Determine transfer function values for the frequency points in step one using this formula.

$$Transf(Freqs)=k\times \frac{\prod \left(z-2\pi j\times Freqs\right)}{\prod \left(p-2\pi j\times Freqs\right)}$$

Determine the discrete FIR filter coefficients using this formula.

$$Coeffs=\left(-{1}^{FilterOrder}\right)\times ifft\left(fftshift\left(Transf\left(Freqs\right)\right)\right)$$

## Extended Capabilities

### C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

## Version History

**Introduced in R2023a**

### R2023a: Lowpass RF, Highpass RF, Bandpass RF, and Bandstop RF Filter blocks have been replaced

Starting in R2023a, the idealized baseband Filter block replaces the Lowpass RF Filter, Highpass RF Filter, Bandpass RF Filter, and Bandstop RF Filter blocks.

When you open a model created before R2023a containing the Lowpass RF Filter, Highpass RF Filter, Bandpass RF Filter, and Bandstop RF Filter Filter blocks, the software replace the old blocks with the new idealized baseband Filter block.

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