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802.11ba WUR Waveform Generation and Analysis

This example shows how to generate IEEE® 802.11ba™ wake-up radio (WUR) packet waveforms. The example also demonstrates how to measure the transmit spectrum mask and spectral flatness.


The 802.11ba standard [ 1 ], referred to as wake-up radio (WUR), defines a mechanism to enable IEEE 802.11 stations (STAs) to operate at extremely low power consumption and to react to incoming traffic with low latency through a wake-up signal. This standard defines two types of WUR PPDU format.

  • WUR Basic PPDU with 20 MHz channel bandwidth (one subchannel)

  • WUR FDMA PPDU with 40 MHz (two subchannels) or 80 MHz (four subchannels) contiguous channel bandwidths

Each 20 MHz subchannel can transmit data for a single user. For each 20 MHz subchannel, the WUR physical layer (PHY) provides support for data rates of 62.5 kb/s and 250 kb/s, indicated as low data rate (LDR) and high data rate (HDR), respectively. Additionally, Annex AC of [ 1 ] provides three examples of symbol sequences and cyclic shift durations (CSDs) at specified data rates.

This example generates 5 WUR packets with a 20 MHz channel bandwidth and 10 microsecond gaps between each of the packets. The example oversamples the waveform using a larger inverse fast Fourier transform (IFFT) length than required for the nominal baseband rate and does not perform spectral filtering. The example then models the effects of a high-power amplifier (HPA), which introduces in-band distortion and spectral regrowth. After HPA modelling, the example extracts the non-WUR portion of the WUR PHY preamble, comprising the L-STF, L-LTF, L-SIG, BPSK-Mark1, and BPSK-Mark2 fields, and the WUR portion, comprising the WUR-Sync and WUR-Data fields, from the generated waveform. The example then performs two transmit spectrum mask measurements for the non-WUR portion of WUR PHY preamble and WUR portion, respectively, and measures the spectral flatness for the WUR portion. This figure shows the workflow contained in this example.

Simulation Setup

Configure the example to generate 5 WUR packets with a 10 microsecond idle period between each packet.

numPackets = 5;
idleTime = 10; % In microseconds

802.11ba WUR Waveform Configuration and Generation

Create a WUR configuration object for a 20 MHz transmission.

numSubchannels = 1; % Number of subchannels
cfgWUR = wlanWURConfig(numSubchannels); % Create WUR packet configuration
cfgWUR.NumTransmitAntennas = 1; % Number of transmit antennas
fs = wlanSampleRate(cfgWUR); % Get the nominal baseband sample rate
osf = 2; % Oversampling factor

Parameterize the transmission by setting WUR configuration object properties for each user. The waveform generator function uses only the first cfgWUR.NumUsers elements of the cfgWUR cell array to generate the corresponding WUR packets.

psdu = cell(1,cfgWUR.NumUsers);
psduLength = [5,10,15,20]; % Bytes, 1 to 22 inclusive for each 20 MHz subchannel
dataRate = {'LDR','HDR','LDR','HDR'};
symDesign = {'Example1','Example2','Example1','Example2'};
rng(0); % Set random state
for i = 1:cfgWUR.NumUsers
    cfgWUR.Subchannel{i}.PSDULength = psduLength(i);
    psdu{i} = randi([0 1],psduLength(i)*8,1,'int8');
    cfgWUR.Subchannel{i}.DataRate = dataRate{i};
    cfgWUR.Subchannel{i}.SymbolDesign = symDesign{i};

Generate the WUR waveform for the specified bits and configuration by using the wlanWaveformGenerator function, setting the number of packets, idle time between each packet, and oversampling factor.

txWaveform = wlanWaveformGenerator(psdu,cfgWUR,'NumPackets',numPackets,'IdleTime',idleTime*1e-6,'OversamplingFactor',osf);

Add Impairments

The HPA introduces nonlinear behaviour in the form of in-band distortion and spectral regrowth. This example simulates the power amplifiers by using the Rapp model, which introduces AM/AM distortion [ 2 ]. Model the amplifier by using the comm.MemorylessNonlinearity object, and configure reduced distortion by specifying a back-off, hpaBackoff, such that the amplifier operates below its saturation point.

pSaturation = 25; % Saturation power of a power amplifier in dBm
hpaBackoff = 15; % Power amplifier backoff in dB
nonLinearity = comm.MemorylessNonlinearity;
nonLinearity.Method = 'Rapp model';
nonLinearity.Smoothness = 3; % p parameter
nonLinearity.LinearGain = -hpaBackoff;
nonLinearity.OutputSaturationLevel = db2mag(pSaturation-30);

Apply the HPA model to the waveform.

txWaveform = nonLinearity(txWaveform);

Add thermal noise to each transmit antenna by using the comm.ThermalNoise object with a noise figure of 6 dB [ 3 ].

thNoise = comm.ThermalNoise('NoiseMethod','Noise Figure','SampleRate',fs*osf,'NoiseFigure',6);
txWaveform = thNoise(txWaveform);

Transmit Spectrum Mask and Spectral Flatness Measurement

Get indices for accessing WUR fields within the time-domain packet.

ind = wlanFieldIndices(cfgWUR,'OversamplingFactor',osf);
% Get the number of samples in the idle time.
numIdle = osf*fs*idleTime*1e-6;
% Define the length of a WUR packet, in samples.
pktLength = double(max(ind.WURData(:,2)))+numIdle;
% Define the length of non-WUR portion of the WUR PHY preamble, composed of the
% L-STF, L-LTF, L-SIG, BPSK-Mark1 and BPSK-Mark2 fields, in samples.
idxPreamble = zeros(ind.BPSKMark2(2),numPackets,'uint32');
% Define the length of the WUR-Sync and WUR-Data fields, in samples.
idxWUR = zeros(max(ind.WURData(:,2))-ind.WURSync(1,1)+1,numPackets,'uint32');

Extract the non-WUR portion of the WUR PHY preamble and WUR portion of each packet within the waveform.

pktOffset = 0; % Start at first sample (no offset)
for i = 1:numPackets
    % Indices of WUR preamble fields
    idxPreamble(:,i) = pktOffset+(1:ind.BPSKMark2(2));
    % Indices of WUR-Sync and WUR-Data fields
    idxWUR(:,i) = pktOffset+(ind.WURSync(1,1):max(ind.WURData(:,2)));
    % Packet offset to generate the end index of each packet
    pktOffset = i*pktLength;
preamFields = txWaveform(idxPreamble(:),:);
wurFields = txWaveform(idxWUR(:),:);

Measure the transmit spectrum mask of the non-WUR portion of the WUR PHY preamble, as specified in Section of [ 1 ].

if numPackets>0
   Spectrum mask passed

Based on the values of limits (in dBr) relative to maximum spectral density of the signal and corresponding frequency offsets (in MHz) provided in Section of [ 1 ], define the transmit spectrum masks of the WUR-Sync and WUR-Data fields for WUR basic and FDMA PPDUs are.

switch numSubchannels
    case 1 % WUR Basic PPDU
        dBrLimits = [-40 -40 -28 -20 -15 0 ...
            0 -15 -20 -28 -40 -40];
        fLimits = [-Inf -30 -20 -11 -3.5 -2.25 ...
            2.25 3.5 11 20 30 Inf];
    case 2 % 40 MHz WUR FDMA PPDU
        dBrLimits = [-40 -40 -28 -20 -15 0 0 -15 -20 ...
            -20 -15 0 0 -15 -20 -28 -40 -40];
        fLimits = [-Inf -60 -40 -21 -13.5 -12.25 -7.75 -6.5 -1 ...
            1 6.5 7.75 12.25 13.5 21 40 60 Inf];
    otherwise % 80 MHz WUR FDMA PPDU
        dBrLimits = [-40 -40 -28 -20 -15 0 0 -15 -20 -20 -15 0 0 -15 -20 ...
            -20 -15 0 0 -15 -20 -20 -15 0 0 -15 -20 -28 -40 -40];
        fLimits = [-Inf -120 -80 -41 -33.5 -32.25 -27.75 -26.5 -21 -19 -13.5 -12.25 -7.75 -6.5 -1 ...
            1 6.5 7.75 12.25 13.5 19 21 26.5 27.75 32.25 33.5 41 80 120 Inf];

Measure the transmit spectrum mask and spectral flatness of the WUR-Sync and WUR-Data fields, as specified in Section and Section of [ 1 ]. The wurTxSpectralFlatnessMeasurement function measures the spectral flatness by comparing the power in any contiguous 1 MHz segment within the center 4 MHz of each 20 MHz channel to the total transmitted power in the center 4 MHz and measures the transmitted power in the manner described in Section of [ 4 ] for equipment with continuous and non-continuous transmissions.

if numPackets>0
    isPassed = wurTxSpectralFlatnessMeasurement(wurFields,fs,osf);
    if isPassed
        fprintf('   Spectral flatness passed\n');
        fprintf('   Spectral flatness failed\n');
   Spectrum mask passed
   Spectral flatness passed

Conclusion and Further Exploration

This example shows how to generate WUR waveforms as specified in the IEEE 802.11ba standard, and measure these quantities.

  • Transmitter spectrum mask

  • Spectral flatness

The HPA model introduces significant in-band distortion and spectral regrowth, which is visible in the spectral mask plot. Try increasing the value of the HPA backoff and observe lower out-of-band emissions. The various patterns of ripple and deviation limits in the spectral flatness measurement is due to the different Multi-Carrier On-Off Keying (MC-OOK) On symbol designs, such as MC-OOK On symbol sequences and CSD values applied. The spectral flatness test will fail for a 20 MHz subchannel if the subchannel in the generated waveform is configured with symbol design and data rate set to 'Example3' and 'HDR', respectively. Try using a different MC-OOK On symbol design and observe the impact on the spectral flatness.


  1. IEEE Std 802.11ba™-2021 - IEEE Standard for Information Technology--Telecommunications and Information Exchange between Systems--Local and Metropolitan Area Networks-Specific Requirements--Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications - Amendment 3: Wake-Up Radio Operation.

  2. R. Porat, et al. TGax Evaluation Methodology, IEEE 11/14-0571r12. 2016-01-21.

  3. Perahia, E., and R. Stacey. Next Generation Wireless LANs: 802.11n and 802.11ac. 2nd Edition. United Kingdom: Cambridge University Press, 2013. Archambault, Jerry, and Shravan Surineni. "IEEE 802.11 spectral measurements using vector signal analyzers." RF Design 27.6 (2004): 38-49.

  4. ETSI EN 300 328 V2.1.1. Wideband transmission systems; Data transmission equipment operating in the 2,4 GHz ISM band and using wide band modulation techniques; Harmonised Standard covering the essential of article 3.2 of Directive 2014/53EU. 2016-11.

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