comm.EVM

Measure error vector magnitude

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Description

Thecomm.EVM(error vector magnitude) System object™ measures the modulator or demodulator performance of an impaired signal.

To measure error vector magnitude:

Define and set up your EVM object. SeeConstruction.
Callstep测量调制器和解调器performance according to the properties ofcomm.EVM. The behavior ofstepis specific to each object in the toolbox.

Note

Starting in R2016b, instead of using thestepmethod to perform the operation defined by the System object, you can call the object with arguments, as if it were a function. For example,y = step(obj,x)andy = obj(x)perform equivalent operations.

Construction

EVM = comm.EVMcreates an error vector magnitude object,EVM. This object measures the amount of impairment in a modulated signal.

EVM = comm.EVM(Name,Value)creates anEVMobject with each specified property set to the specified value. You can specify additional name-value pair arguments in any order as (Name1,Value1,...,NameN,ValueN).

Example:EVM = comm.EVM('ReferenceSignalSource','Estimated from reference constellation')creates an object,EVM, that measures the RMS EVM of a received signal by using a reference constellation.

Properties

`Normalization`	Normalization method Normalization method used in EVM calculation, specified as one of the following:`'Average reference signal power'`(default),`'Average constellation power'`, or`'Peak constellation power'`.
`AverageConstellationPower`	Average constellation power Average constellation power, specified in watts as a positive real scalar. This property is available when`Normalization`is`'Average constellation power'`. The default is`1`.
`PeakConstellationPower`	Peak constellation power Peak constellation power, specified in watts as a positive real scalar. This property is available when`Normalization`is`'Peak constellation power'`. The default is`1`.
`ReferenceSignalSource`	Reference signal source Reference signal source, specified as either`'Input port'`(default) or`'Estimated from reference constellation'`. To provide an explicit reference signal against which the input signal is measured, set this property to`'Input port'`. To measure the EVM of the input signal against a reference constellation, set this property to`'Estimated from reference constellation'`.
`ReferenceConstellation`	Reference constellation Reference constellation, specified as a vector. This property is available when the`ReferenceSignalSource`property is`'Estimated from reference constellation'`. The default is`[0.7071 - 0.7071i; -0.7071 - 0.7071i; -0.7071 + 0.7071i; 0.7071 + 0.7071i]`, which corresponds to a standard QPSK constellation. You can derive constellation points by using modulation functions or objects. For example, to derive the reference constellation for a 16-QAM signal, you can use`qammod(0:15,16)`.
`MeasurementIntervalSource`	Measurement interval source Measurement interval source, specified as one of the following:`'Input length'`(default),`'Entire history'`,`'Custom'`, or`'Custom with periodic reset'`. This property affects the RMS and maximum EVM outputs only. To calculate EVM using only the current samples, set this property to`'Input length'`. To calculate EVM for all samples, set this property to`'Entire history'`. To calculate EVM over an interval you specify and to use a sliding window, set this property to`'Custom'`. To calculate EVM over an interval you specify and to reset the object each time the measurement interval is filled, set this property to`'Custom with periodic reset'`.
`MeasurementInterval`	Measurement interval 测量时间间隔对挣值管理的都是它ted, specified in samples as a real positive integer. This property is available when`MeasurementIntervalSource`is`'Custom'`or`'Custom with periodic reset'`. The default is`100`.
`AveragingDimensions`	Averaging dimensions Averaging dimensions over which to average the EVM measurements, specified as an integer or row vector of integers with element values in the range [1, 3]. For example, to average across the rows, set this property to`2`. The default is`1`. The object supports variable-size inputs over the dimensions in which the averaging takes place. However, the input size for the nonaveraged dimensions must remain constant between calls of the object. For example, if the input has size`[4 3 2]`and`Averaging dimensions`is`[1 3]`, the output size is`[1 3 1]`, and the second dimension must remain fixed at`3`.
`MaximumEVMOutputPort`	Maximum EVM measurement output port Maximum EVM measurement output port, specified as a logical scalar. To create an output port for maximum EVM measurements, set this property to`true`. The default is`false`.
`XPercentileEVMOutputPort`	X-percentile EVM measurement output port X-percentile EVM measurement output port, specified as a logical scalar. To create an output port forX-percentile EVM measurements, set this property to`true`. TheX-percentile EVM measurements persist until you reset the object. These measurements are calculated by using all of the input frames since the last reset. The default is`false`.
`XPercentileValue`	X-percentile value X-percentile value below whichX% of the EVM measurements fall, specified as a real scalar from`0`to`100`. This property is available when`XPercentileEVMOutputPort`is`true`. The default is`95`.
`SymbolCountOutputPort`	Symbol count output port Symbol count output port, specified as a logical scalar. To output the number of accumulated symbols used to calculate theX-percentile EVM measurements, set this property to`true`. This property is available when`XPercentileEVMOutputPort`is`true`. The default is`false`.

Methods

step	Measure error vector magnitude

Common to All System Objects
`release`	Allow System object property value changes
`reset`	Reset internal states of System object

Examples

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Measure EVM of Noisy 16-QAM Modulated Signal

Open Live Script

Create an EVM object. Configure it using name-value pairs to output maximum EVM, 90th percentile EVM, and the symbol count.

evm = comm.EVM('MaximumEVMOutputPort',true,...'XPercentileEVMOutputPort',true,'XPercentileValue',90,...'SymbolCountOutputPort',true);

Generate random data symbols. Apply 16-QAM modulation. The modulated signal serves as the reference for the subsequent EVM measurements.

data = randi([0 15],1000,1); refSym = qammod(data,16,'UnitAveragePower',true);

Pass the modulated signal through an AWGN channel.

rxSym = awgn(refSym,20);

Measure the EVM of the noisy signal.

[rmsEVM,maxEVM,pctEVM,numSym] = evm(refSym,rxSym)

rmsEVM = 9.8775

maxEVM = 26.8385

pctEVM = 14.9750

numSym = 1000

Estimate Received EVM

Open Live Script

Generate filtered QAM data and pass it through an AWGN channel. Compute the symbol error rate, and estimate the EVM of the received signal.

Create channel and filter System objects™.

M = 16; refConst = qammod(0:M-1,M); channel = comm.AWGNChannel('NoiseMethod','Signal to noise ratio (SNR)',...'SNR',15,'SignalPower',10); txfilter = comm.RaisedCosineTransmitFilter('OutputSamplesPerSymbol',4); rxfilter = comm.RaisedCosineReceiveFilter('InputSamplesPerSymbol',4,...'DecimationFactor',4);

Create an EVM object to output RMS and maximum EVM measurements.

evm = comm.EVM('MaximumEVMOutputPort',true,...'ReferenceSignalSource','Estimated from reference constellation',...'ReferenceConstellation',refConst);

Create an error rate object and account for the signal delay through the transmit and receive filters. For a filter, the group delay is equal to 1/2 of theFilterSpanInSymbolsproperty.

rxd = (txfilter.FilterSpanInSymbols + rxfilter.FilterSpanInSymbols)/2; errorRate = comm.ErrorRate('ReceiveDelay',rxd);

Perform the following channel operations:

Generate random data symbols.
Apply 16-QAM modulation.
Filter the modulated data through a raised cosine Tx filter.
Pass the transmitted signal through an AWGN channel.
Filter the received data through a raised cosine Rx filter.
Demodulate the filtered data.

txData = randi([0 15],1000,1); modData = qammod(txData,M); txSig = txfilter(modData); rxSig = channel(txSig); filtSig = rxfilter(rxSig); rxData = qamdemod(filtSig,M);

计算误差统计和显示符号bol error rate.

errStats = errorRate(txData,rxData); symErrRate = errStats(1)

symErrRate = 0.0222

Measure and display the received RMS EVM and maximum EVM values. Take the filter delay into account by deleting the firstrxd+1symbols. Because there are symbol errors, the EVM may not be totally accurate.

[rmsEVM,maxEVM] = evm(filtSig(rxd+1:end))

rmsEVM = 17.2966

maxEVM = 40.1595

Measure EVM Using Reference Constellation

Open Live Script

Generate random data symbols, and apply 8-PSK modulation.

d = randi([0 7],2000,1); txSig = pskmod(d,8,pi/8);

Pass the modulated signal through an AWGN channel.

rxSig = awgn(txSig,30);

Create an EVM object. Measure the RMS EVM using the transmitted signal as the reference.

evm = comm.EVM; rmsEVM1 = evm(txSig,rxSig);

Release the EVM object. Configure the object to estimate the EVM of the received signal against a reference constellation.

release(evm) evm.ReferenceSignalSource ='Estimated from reference constellation'; evm.ReferenceConstellation = pskmod(0:7,8,pi/8);

Measure the RMS EVM using only the received signal as an input. Verify that it matches the result obtained when using a reference signal.

rmsEVM2 = evm(rxSig); [rmsEVM1 rmsEVM2]

ans =1×23.1524 3.1524

Measure EVM Using Custom Measurement Interval

Open Live Script

Measure the EVM of a noisy 8-PSK signal using two types of custom measurement intervals. Display the results.

Set the number of frames,M, and the number of subframes per frame,K.

M = 2; K = 5;

Set the number of symbols in a subframe. Calculate the corresponding frame length.

sfLen = 100; frmLen = K*sfLen

frmLen = 500

Create an EVM object. Configure the object to use a custom measurement interval equal to the frame length.

evm1 = comm.EVM('MeasurementIntervalSource','Custom',...'MeasurementInterval',frmLen);

Configure the object to measure EVM using an 8-PSK reference constellation.

evm1.ReferenceSignalSource ='Estimated from reference constellation'; evm1.ReferenceConstellation = pskmod(0:7,8,pi/8);

Create an EVM object, and configure it use a 500-symbol measurement interval with a periodic reset. Configure the object to measure EVM using an 8-PSK reference constellation.

evm2 = comm.EVM('MeasurementIntervalSource','Custom with periodic reset',...'MeasurementInterval',frmLen); evm2.ReferenceSignalSource ='Estimated from reference constellation'; evm2.ReferenceConstellation = pskmod(0:7,8,pi/8);

Initialize the EVM and signal-to-noise arrays.

rmsEVM1 = zeros(K,M); rmsEVM2 = zeros(K,M); snrdB = zeros(K,M);

Measure the EVM for a noisy 8-PSK signal using both objects. The SNR increases by 1 dB from subframe to subframe. Forevm1, the 500 most recent symbols are used to compute the estimate. In this case, a sliding window is used so that an entire frame of data is always processed. Forevm2, the symbols are cleared each time a new frame is encountered.

form = 1:Mfork = 1:K data = randi([0 7],sfLen,1); txSig = pskmod(data,8,pi/8); snrdB(k,m) = k+(m-1)*K+7; rxSig = awgn(txSig,snrdB(k,m)); rmsEVM1(k,m) = evm1(rxSig); rmsEVM2(k,m) = evm2(rxSig);endend

Display the EVM measured using the two approaches. The windowing used in the first case provides an averaging across the subframes. In the second case, the EVM object resets after the first frame so that the calculated EVM values more accurately reflect the current SNR.

stairs(snrdB(:),[rmsEVM1(:) rmsEVM2(:)]) xlabel('SNR (dB)') ylabel('EVM (%)') legend('No Reset','Periodic Reset')

Figure contains an axes object. The axes object contains 2 objects of type stair. These objects represent No Reset, Periodic Reset.

Measure EVM Across Different Dimensions

Open Live Script

Create OFDM modulator and demodulator objects.

ofdmmod = comm.OFDMModulator('FFTLength',32,'NumSymbols',4); ofdmdemod = comm.OFDMDemodulator('FFTLength',32,'NumSymbols',4);

Determine the number of subcarriers and symbols in the OFDM signal.

ofdmDims = info(海底钻井mmod); numSC = ofdmDims.DataInputSize(1)

numSC = 21

numSym = ofdmDims.DataInputSize(2)

numSym = 4

Generate random symbols and apply QPSK modulation.

msg = randi([0 3],numSC,numSym); modSig = pskmod(msg,4,pi/4);

OFDM modulate the QPSK signal. Pass the signal through an AWGN channel. Demodulate the noisy signal.

txSig = ofdmmod(modSig); rxSig = awgn(txSig,10,'measured'); demodSig = ofdmdemod(rxSig);

Create an EVM object, where the result is averaged over the subcarriers. Measure the EVM. There are four entries corresponding to each of the 4 OFDM symbols.

evm = comm.EVM('AveragingDimensions',1); rmsEVM = evm(demodSig,modSig)

rmsEVM =1×427.4354 23.6279 22.6772 23.1699

Overwrite the EVM object, where the result is averaged over the OFDM symbols. Measure the EVM. There are 21 entries corresponding to each of the 21 subcarriers.

evm = comm.EVM('AveragingDimensions',2); rmsEVM = evm(demodSig,modSig)

rmsEVM =21×128.8225 17.8536 18.6809 20.8872 22.3532 24.7197 30.1954 33.4899 36.2847 21.4230 ⋮

Measure the EVM and average over both the subcarriers and the OFDM symbols.

evm = comm.EVM('AveragingDimensions',[1 2]); rmsEVM = evm(demodSig,modSig)

rmsEVM = 24.2986

Plot Time-Varying EVM for OFDM Signal

Open Script

Calculate and plot the EVM of an OFDM signal. The signal consists of two packets separated by an interval.

Create System objects to:

OFDM modulate a signal
Introduce phase noise
Plot time-varying signals

ofdmmod = comm.OFDMModulator('FFTLength',256,'NumSymbols',2); pnoise = comm.PhaseNoise('Level',-60,'FrequencyOffset',20,'SampleRate',1000); tscope = timescope('YLabel','EVM (%)','YLimits',[0 40],...'SampleRate',1000,'TimeSpanSource','Property','TimeSpan',1.2,...'ShowGrid',true);

Create an EVM object. To generate a time-varying estimate of the EVM, set theAveragingDimensionsproperty to2.

evm = comm.EVM('MaximumEVMOutputPort',false,...'ReferenceSignalSource','Input port',...'AveragingDimensions',2);

Determine the input data dimensions of the OFDM modulator.

modDims = info(ofdmmod)

modDims = struct with fields: DataInputSize: [245 2] OutputSize: [544 1]

Create QPSK-modulated random data for the first packet. Apply OFDM modulation.

data = randi([0 3],modDims.DataInputSize); qpskSig = pskmod(data,4,pi/4); txSig1 = ofdmmod(qpskSig);

Create a second data packet.

data = randi([0 3],modDims.DataInputSize); qpskSig = pskmod(data,4,pi/4); txSig2 = ofdmmod(qpskSig);

Concatenate the two packets and include an interval in which nothing is transmitted.

txSig = [txSig1; zeros(112,1); txSig2];

Apply I/Q amplitude and phase imbalance to the transmitted signal.

rxSigIQimb = iqimbal(txSig,2,5);

Apply phase noise.

rxSig = pnoise(rxSigIQimb);

Measure the EVM of the received signal, and plot its time-varying EVM.

e = evm(txSig,rxSig); tscope(e)

Algorithms

Both the EVM block and the EVM object provide three normalization methods. You can normalize measurements according to the average power of the reference signal, average constellation power, or peak constellation power. Different industry standards follow one of these normalization methods.

The block or object calculates the RMS EVM value differently for each normalization method.

EVM Normalization Method	Algorithm
Reference signal	$E V M_{R M S} = \sqrt{\frac{\frac{1}{N} \sum_{k = 1}^{N} (e_{k})}{\frac{1}{N} \sum_{k = 1}^{N} (I_{k}^{2} + Q_{k}^{2})}} * 100$
Average power	$E V M_{RMS} (%) = 100 \sqrt{\frac{\frac{1}{N} \sum_{k = 1}^{N} (e_{k})}{P_{avg}}}$
Peak power	$E V M_{RMS} (%) = 100 \sqrt{\frac{\frac{1}{N} \sum_{k = 1}^{N} (e_{k})}{P_{max}}}$

EVM Normalization Method

Algorithm

Reference signal

$E V M_{R M S} = \sqrt{\frac{\frac{1}{N} \sum_{k = 1}^{N} (e_{k})}{\frac{1}{N} \sum_{k = 1}^{N} (I_{k}^{2} + Q_{k}^{2})}} * 100$

Average power

$E V M_{RMS} (%) = 100 \sqrt{\frac{\frac{1}{N} \sum_{k = 1}^{N} (e_{k})}{P_{avg}}}$

Peak power

$E V M_{RMS} (%) = 100 \sqrt{\frac{\frac{1}{N} \sum_{k = 1}^{N} (e_{k})}{P_{max}}}$

Where:

e_k= $e_{k} = {(I_{k} - {\tilde{I}}_{k})}^{2} + {(Q_{k} - {\tilde{Q}}_{k})}^{2}$
I_kis the in-phase measurement of the kth symbol in the burst
Q_kis the quadrature phase measurement of the kth symbol in the burst
Nis the input vector length
P_avgis the average constellation power
P_maxis the peak constellation power
I_kandQ_krepresent ideal (reference) values. ${\tilde{I}}_{k}$ and ${\tilde{Q}}_{k}$ represent measured (received) symbols.

The max EVM is the maximum EVM value in a frame or ${EVM}_{max} = max_{k \in [1, ..., N]} {{EVM}_{k}},$ where k is the kth symbol in a burst of lengthN.

The definition for EVM_kvaries depending upon which normalization method you select for computing measurements. The block or object supports these algorithms.

EVM Normalization	Algorithm
Reference signal	$E V M_{k} = \sqrt{\frac{e_{k}}{\frac{1}{N} \sum_{k = 1}^{N} (I_{k}^{2} + Q_{k}^{2})}} * 100$
Average power	$E V M_{k} = 100 \sqrt{\frac{e_{k}}{P_{avg}}}$
Peak power	$E V M_{k} = 100 \sqrt{\frac{e_{k}}{P_{max}}}$

EVM Normalization

Algorithm

Reference signal

$E V M_{k} = \sqrt{\frac{e_{k}}{\frac{1}{N} \sum_{k = 1}^{N} (I_{k}^{2} + Q_{k}^{2})}} * 100$

Average power

$E V M_{k} = 100 \sqrt{\frac{e_{k}}{P_{avg}}}$

Peak power

$E V M_{k} = 100 \sqrt{\frac{e_{k}}{P_{max}}}$

The block or object computes theX-percentile EVM by creating a histogram of all the incomingEVM_kvalues. The output provides the EVM value below which X% of the EVM values fall.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

SeeSystem Objects in MATLAB Code Generation(MATLAB Coder).

comm.EVM

Description

Construction

Properties

Methods

Examples

Measure EVM of Noisy 16-QAM Modulated Signal

Estimate Received EVM

Measure EVM Using Reference Constellation

Measure EVM Using Custom Measurement Interval

Measure EVM Across Different Dimensions

Plot Time-Varying EVM for OFDM Signal

Algorithms

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

See Also

Communications Toolbox Documentation

万博1manbetx

Bridging Wireless Communications Design and Testing with MATLAB

comm.EVM

Description

Construction

Properties

Methods

Examples

Measure EVM of Noisy 16-QAM Modulated Signal

Estimate Received EVM

Measure EVM Using Reference Constellation

Measure EVM Using Custom Measurement Interval

Measure EVM Across Different Dimensions

Plot Time-Varying EVM for OFDM Signal

Algorithms

Extended Capabilities

C/C++ Code GenerationGenerate C and C++ code using MATLAB® Coder™.

See Also

Communications Toolbox Documentation

万博1manbetx

Bridging Wireless Communications Design and Testing with MATLAB

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.