powermeter

Measure power of voltage signal

Description

The powermeter System object™ computes the power measurements of a voltage signal. The power measurements include average power, peak power, and peak-to-average power ratio. The object uses the sliding window method to compute these measurements. For more details, see Algorithms.

To measure the power of a voltage signal:

1. Create the powermeter object and set its properties.

2. 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

Syntax

meter = powermeter

meter = powermeter(Len,Overlap,Name=Value)

meter = powermeter(Name=Value)

Description

meter = powermeter returns a powermeter system object that computes power, peak-to-average power ratio (PAPR), and the complementary cumulative distribution function (CCDF) of the power of voltage signal. The CCDF helps find the probability that the instantaneous signal power exceeds a specified level above the average signal power.

meter = powermeter(Len,Overlap,Name=Value) sets the WindowLength property to Len and the OverlapLength property to Overlap. To enable this syntax, set the ComputeCCDF property to false.

meter = powermeter(Name=Value) returns a powermeter system object with each specified property set to the specified value. Enclose each property name in quotes. You can use this syntax with the previous input argument.

Properties

Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

Measurement — Desired power measurement

'Average power' (default) | 'Peak power' | 'Peak-to-average power ratio' | 'All'

Desired power measurement, specified as 'Average power', 'Peak power', 'Peak-to-average power ratio' or 'All'.

ReferenceLoad — Reference load

1 (default) | positive scalar

Reference load used by the power meter to compute the power values in ohms, specified as a positive scalar.

Tunable: Yes

Data Types: single | double

ComputeCCDF — Compute CCDF

false or 0 (default) | true or 1

Check whether to calculate CCDF, specified as logical 0 (false) or 1 (true). When ComputeCCDF property is true:

• All input samples since object creation or reset are used to collect statistics.

• The WindowLength and OverlapLength properties become read-only and are set to Inf and 0 respectively.

Data Types: logical

PowerRange — Power range

50 (default) | positive scalar

The x-axis range of the computed CCDF curves in dB, specified as a positive scalar. The computed CCDF curves end at the maximum relative power, namely, peak-to-average power ratio of the signal, and start at PAPR - PowerRange. For the CCDF capability of the powermeter object, relative power is the ratio of instantaneous signal power to average signal power in dB.

Dependencies

To enable this property, set the ComputeCCDF property to true or 1.

Data Types: single | double

PowerResolution — Power Resolution

0.1 (default) | positive scalar in ohms

The x-axis resolution of the computed CCDF curves in dB, specified as a positive scalar.

Dependencies

To enable this property, set the ComputeCCDF property to true or 1.

Data Types: single | double

WindowLength — Window length

256 (default) | nonnegative integer

Sliding window length over which the measurement is computed, specified as a nonnegative integer.

Dependencies

If the ComputeCCDF property is true or 1, then WindowLength property is set to Inf and is read-only.

Data Types: double

OverlapLength — Overlap length between windows

WindowLength − 1 (default) | nonnegative integer

Overlap length between sliding windows, specified as a nonnegative integer. The value of overlap length varies in the range [0, WindowLength − 1]. If not specified, the overlap length is WindowLength − 1.

Dependencies

If the ComputeCCDF property is true or 1, then OverlapLength property is set to 0 and is read-only.

Data Types: double

OutputPowerUnits — Output power units

'dBm' (default) | 'dBW' | 'Watts'

Units of the measured power values, specified as 'dBm', 'dBW', or 'Watts'.

Usage

Syntax

avgpwr = meter(x)

peakpwr = meter(x)

papr = meter(x)

[avgpwr,peakpwr,papr] = meter(x)

Description

avgpwr = meter(x) computes the average power of the input signal x when the Measurement property is set to 'Average power'. Each column of x is an independent channel. The object computes the average power of each channel of the input signal independently.

peakpwr = meter(x) computes the peak power of the input signal x when the Measurement property is set to 'Peak power'. Each column of x is an independent channel. The object computes the peak power of each channel of the input signal independently.

papr = meter(x) computes the peak-to-average power ratio of the input signal x when the Measurement property is set to 'Peak-to-average power ratio'. Each column of x is an independent channel. The object computes the peak-to-average power ratio of each channel of the input signal independently.

[avgpwr,peakpwr,papr] = meter(x) computes the average power, peak power, and the peak-to-average power ratio of the input signal x when the Measurement property is set to 'All'. Each column of x is an independent channel. The object computes the power measurements of each channel of the input signal independently.

Input Arguments

x — Input voltage signal

vector | matrix

Input voltage signal, specified as a vector or a matrix, and measured in volts. If x is a matrix, each column is treated as an independent channel. The power measurement is computed along each channel using the Sliding Window Method.

The object also accepts variable-size inputs. That is, once the object is locked, you can change the size of each input channel, but you cannot change the number of channels.

Data Types: single | double
Complex Number Support: Yes

Output Arguments

avgpwr — Average power

vector | matrix

Average power of the voltage signal, returned as a vector or a matrix, and measured in the units determined by the PowerUnits property. For details on how the object computes the average power, see Average Power.

Data Types: single | double

peakpwr — Peak power

vector | matrix

Peak power of the voltage signal, returned as a vector or a matrix, and measured in the units determined by the PowerUnits property. For details on how the object computes the peak power, see Peak Power.

Data Types: single | double

papr — Peak-to-average power ratio

vector | matrix

Peak-to-average power ratio of the voltage signal, returned as a vector or a matrix. For details on how the object computes the peak-to-average power ratio, see Peak-to-Average Power Ratio.

Data Types: single | double

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)

Specific to powermeter

plotCCDF	Plot CCDF curves
ccdf	Get coordinates of CCDF curves
relativePower	Use CCDF to find relative power for specified probability
probability	Use CCDF to find probability for specified relative power

Common to All System Objects

step	Run System object algorithm
release	Release resources and allow changes to System object property values and input characteristics
reset	Reset internal states of System object

Examples

Compute Power Measurements of Voltage Signal

Compute the power measurements of a noisy sinusoidal signal using a power meter. These measurements include average power, peak power, and peak-to-average power ratio.

Assume the maximum voltage of the signal to be 100 V. The instantaneous values of a sinusoidal waveform are given by the equation $\mathrm{Vi}=\mathrm{Vmax}\times \sin \left(2\pi \mathrm{ft}\right)$, where$$Vi$$ is the instantaneous value, $$Vmax$$ is the maximum voltage of the signal, and $\mathit{f}$ is the frequency of the signal in Hz.

Initialization

The input signal is a sum of two sine waves with frequencies set to 1 kHz and 10 kHz, respectively. The frame length and the sampling frequency of the generated signal is 512 samples and 44.1 kHz, respectively.

To measure the power in this signal, create a powermeter object. Set 'Measurement' to 'All'. This setting enables the object to measure the average power, peak power, and peak-to-average power ratio. Set the length of the sliding window to 16 samples and the reference load to 50 Ohms. Use this object to measure the power in dBm units. Visualize the power measurements using the timescope object.

FrameLength = 512;
Fs = 44.1e3;
A = 100;
sine1 = dsp.SineWave('Amplitude',A, ...
    'Frequency',1e3, ...
    'SampleRate',44.1e3, ...
    'SamplesPerFrame',FrameLength);
sine2 = dsp.SineWave('Amplitude',A, ...
    'Frequency',10e3, ...
    'SampleRate',44.1e3, ...
    'SamplesPerFrame',FrameLength);
pm  = powermeter(16, 'Measurement', 'All', ...
                     'ReferenceLoad', 50, ...
                     'PowerUnits', 'dBm');
scope  = timescope('NumInputPorts',4,'SampleRate',Fs, ...
                   'TimeSpanSource','property', ...
                   'TimeSpan',96, ...
                   'YLabel','dBm', ...
                   'YLimits',[-30 90]);
title = 'Power Measurements';
scope.ChannelNames = {'Average power', ...
    'Peak power','Peak-to-average power ratio', ...
    'Expected Average Power'};
scope.Title = title;

Compute the Power Measurements

Add zero-mean white Gaussian noise with a standard deviation of 0.001 to the sum of sine waves. Vary the amplitude of the sine waves. Measure the average power, peak power, and the peak-to-average power ratio of this noisy sinusoidal signal that has a varying amplitude. For details on how the object measures these power values, see Algorithms. Compare the measured values to the expected value of the average power.

The expected value of the average power $\mathit{P}$ of the noisy sinusoidal signal is given by the following equation.

$$\mathit{P}=\frac{{\mathit{A}}_1^2}{2\mathit{R}}+\frac{{\mathit{A}}_2^2}{2\mathit{R}}+\mathrm{var}\left(\mathrm{noise}\right),$$

where,

• ${\mathit{A}}_1$ is the amplitude of the first sinusoidal signal.

• ${\mathit{A}}_2$ is the amplitude of the second sinusoidal signal.

• $\mathit{R}$ is the reference load in ohms.

In dBm, the expected power is computed using the following equation:

$${\mathrm{expPwr}}_{\mathrm{dBm}}=10{\log }_{10}\left(\mathit{P}\right)+30.$$

Compare the expected value with the value computed by the object. All values are in dBm. These values match very closely. To verify, view the computed measurements using the timescope object.

Vect = [1/8 1/2 1 2 1 1/2 1/8 1/16 1/32];
for index = 1:length(Vect)
    V = Vect(index);
    for i = 1:1000
        x = V*sine1()+V*sine2()+0.001.*randn(FrameLength,1);
        P = (((V*A)^2)/100)+(((V*A)^2)/100)+(0.001)^2;
        expPwr = (10*log10(P)+30)*ones(FrameLength,1);
        [avgPwr,pkPwr,papr] = pm(x);
        scope(avgPwr,pkPwr,papr,expPwr);
    end
end

Algorithms

Sliding Window Method

In the sliding window method, the power measurement is computed over a finite duration of the signal. The window length defines the length of the data over which the algorithm computes the power value. The window moves as the new data comes in. The output for each input sample is the measurement done over the current sample and the Len – 1 previous samples. Len is the length of the sliding window in samples. To compute the first Len – 1 outputs, when the window does not have enough data yet, the algorithm fills the window with zeros. As an example, to compute the average power when the second input sample comes in, the algorithm fills the window with Len – 2 zeros. The input signal x is then the two data samples followed by Len – 2 zeros.

For a more detailed example, see Sliding Window Method.

If the window is large, the power computed is closer to the stationary power of the data. For data that does not change rapidly, use a long window to get a smoother measurement. For data that changes fast, use a smaller window.

Average Power

The average power of the voltage signal is computed using the Sliding Window Method and is given by the following equations:

$$AvgPowe{r}_{dBm}=10{\log }_{10}\left(\mathrm{movAvg}\left({\left|x\right|}^2\right)/R\right)+30$$

$$AvgPowe{r}_{dBW}=10{\log }_{10}\left(\mathrm{movAvg}\left({\left|x\right|}^2\right)/R\right)$$

$$AvgPowe{r}_{Watts}=\mathrm{movAvg}\left({\left|x\right|}^2\right)/R$$

where,

• x is the input voltage signal.

• R is the reference load (in ohms) that is used to compute the power value.

• movAvg computes the moving average using the sliding window method. The powermeter object in MATLAB^® uses the dsp.MovingAverage object and the Power Meter block in Simulink^® uses the Moving Average block.

Peak Power

The peak power of the voltage signal is computed using the Sliding Window Method and is given by the following equations:

$$PeakPowe{r}_{dBm}=10{\log }_{10}\left(\mathrm{movMax}\left({\left|x\right|}^2\right)/R\right)+30$$

$$PeakPowe{r}_{dBW}=10{\log }_{10}\left(\mathrm{movMax}\left({\left|x\right|}^2\right)/R\right)$$

$$PeakPowe{r}_{Watts}=\mathrm{movMax}\left({\left|x\right|}^2\right)/R$$

where,

• x is the input voltage signal.

• R is the reference load (in ohms) that is used to compute the power value.

• movMax computes the moving maximum using the sliding window method. The powermeter object in MATLAB uses the dsp.MovingMaximum object and the Power Meter block in Simulink uses the Moving Maximum block.

Peak-to-Average Power Ratio

The peak-to-average power ratio of the voltage signal is computed using the Sliding Window Method and is given by the following equations:

$$pkAvgPw{r}_{dBm}=10{\log }_{10}\left(\mathrm{movMax}\left({\left|x\right|}^2\right)/\mathrm{movAvg}\left({\left|x\right|}^2\right)\right)$$

$$pkAvgPw{r}_{dBW}=10{\log }_{10}\left(\mathrm{movMax}\left({\left|x\right|}^2\right)/\mathrm{movAvg}\left({\left|x\right|}^2\right)\right)$$

$$pkAvgPw{r}_{Watts}=\mathrm{movMax}\left({\left|x\right|}^2\right)/\mathrm{movAvg}\left({\left|x\right|}^2\right)$$

where,

• x is the input voltage signal.

• movAvg computes the moving average using the sliding window method. The powermeter object in MATLAB uses the dsp.MovingAverage object and the Power Meter block in Simulink uses the Moving Average block.

• movMax computes the moving maximum using the sliding window method. The powermeter object in MATLAB uses the dsp.MovingMaximum object and the Power Meter block in Simulink uses the Moving Maximum block.

Extended Capabilities

C/C++ Code Generation

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

Usage notes and limitations:

See System Objects in MATLAB Code Generation (MATLAB Coder).

Version History

Introduced in R2021a