wlanHTLTFChannelEstimate

R2026b

Channel estimation using HT-LTF

Syntax

chanEst = wlanHTLTFChannelEstimate(demodSig,cfg)

chanEst = wlanHTLTFChannelEstimate(demodSig,cfg,span)

Description

chanEst = wlanHTLTFChannelEstimate(demodSig,cfg) returns the channel estimate using the demodulated HT-LTF signal, demodSig, given the parameters specified in configuration object cfg.

chanEst = wlanHTLTFChannelEstimate(demodSig,cfg,span) returns the channel estimate and specifies the span of a moving-average filter used to perform frequency smoothing.

Examples

Estimate SISO Channel Using HT-LTF

Estimate and plot the channel coefficients of an HT-mixed format channel by using the high throughput long training field.

Create an HT format configuration object. Generate the corresponding HT-LTF based on the object.

cfg = wlanHTConfig;
txSig = wlanHTLTF(cfg);

Multiply the transmitted HT-LTF signal by 0.2 + 0.1i and pass it through an AWGN channel. Demodulate the received signal.

rxSig = awgn(txSig*(0.2+0.1i),30);
demodSig = wlanHTLTFDemodulate(rxSig,cfg);

Estimate the channel response using the demodulated HT-LTF.

chanEst = wlanHTLTFChannelEstimate(demodSig,cfg);

Plot the channel estimate.

scatterplot(chanEst)
grid

The channel estimate matches the complex channel multiplier.

Estimate MIMO Channel Using HT-LTF

Estimate the channel coefficients of a 2x2 MIMO channel by using the high throughput long training field. Recover the HT-data field and determine the number of bit errors.

Create an HT-mixed format configuration object for a channel having two spatial streams and four transmit antennas. Transmit a complete HT waveform.

cfg = wlanHTConfig('NumTransmitAntennas',2, ...
    'NumSpaceTimeStreams',2,'MCS',11);
txPSDU = randi([0 1],8*cfg.PSDULength,1);
txWaveform = wlanWaveformGenerator(txPSDU,cfg);

Pass the transmitted waveform through a 2x2 TGn channel.

tgnChan = wlanTGnChannel('SampleRate',20e6, ...
    'NumTransmitAntennas',2, ...
    'NumReceiveAntennas',2, ...
    'LargeScaleFadingEffect','Pathloss and shadowing', ...
    'NormalizeChannelOutputs',false);
rxWaveformNoNoise = tgnChan(txWaveform);

Add AWGN to the received signal.

snrdB = 80; % SNR (dB)
% Convert the SNR per active subcarrier to total SNR to account for noise energy in null subcarriers
ofdmInfo = wlanHTOFDMInfo("HT-LTF",cfg);
snrValue = convertSNR(snrdB,"snrsc","snr",FFTLength=ofdmInfo.FFTLength,NumActiveSubcarriers=ofdmInfo.NumTones);
nVar = 10^((-snrValue-30)/10); % Noise variance (W) for 0 dBm (-30 dBW) signal power
rxWaveform = awgn(rxWaveformNoNoise,snrValue);

Determine the indices for the HT-LTF. Extract the HT-LTF from the received waveform. Demodulate the HT-LTF.

indLTF  = wlanFieldIndices(cfg,'HT-LTF');
rxLTF = rxWaveform(indLTF(1):indLTF(2),:);
ltfDemodSig = wlanHTLTFDemodulate(rxLTF,cfg);

Generate the channel estimate by using the demodulated HT-LTF signal. Specify a smoothing filter span of three subcarriers.

chanEst = wlanHTLTFChannelEstimate(ltfDemodSig,cfg,3);

Extract the HT-data field from the received waveform.

indData = wlanFieldIndices(cfg,'HT-Data');
rxDataField = rxWaveform(indData(1):indData(2),:);

Recover the data and verify that there no bit errors occurred.

rxPSDU = wlanHTDataRecover(rxDataField,chanEst,nVar,cfg);

numErrs = biterr(txPSDU,rxPSDU)

numErrs = 
0

Input Arguments

demodSig — Demodulated HT-LTF signal

3-D array

Demodulated HT-LTF signal, specified as an N_ST-by-N_SYM-by-N_R array. N_ST is the number of occupied subcarriers, N_SYM is the number of HT-LTF OFDM symbols, and N_R is the number of receive antennas.

Data Types: single | double
Complex Number Support: Yes

cfg — Configuration information

wlanHTConfig object

Configuration information, specified as a wlanHTConfig object.

span — Filter span

positive odd integer

Filter span of the frequency smoothing filter, specified as a positive odd integer and expressed as a number of subcarriers. Frequency smoothing is applied only when span is specified and greater than one. See Frequency Smoothing.

Data Types: single | double

Output Arguments

chanEst — Channel estimate

3-D array

Channel estimate between all combinations of space-time streams and receive antennas, returned as an N_ST-by-(N_STS+N_ESS)-by-N_R array. N_ST is the number of occupied subcarriers, N_STS is the number of space-time streams. N_ESS is the number of extension spatial streams. N_R is the number of receive antennas. Data and pilot subcarriers are included in the channel estimate.

Data Types: single | double
Complex Number Support: Yes

More About

HT-LTF

The high throughput long training field (HT-LTF) is located between the HT-STF and data field of an HT-mixed packet. This diagram¹ shows the HT-LTF in an HT-mixed packet.

As described in Section 19.3.9.4.6 of IEEE^® Std 802.11™-2016, the receiver can use the HT-LTF to estimate the MIMO channel between the set of QAM mapper outputs (or, if STBC is applied, the STBC encoder outputs) and the receive chains. The HT-LTF portion has one or two parts. The first part consists of one, two, or four HT-LTFs that are necessary for demodulation of the HT-Data portion of the PPDU. These HT-LTFs are referred to as HT-DLTFs. The optional second part consists of zero, one, two, or four HT-LTFs that can be used to sound extra spatial dimensions of the MIMO channel not utilized by the HT-Data portion of the PPDU. These HT-LTFs are referred to as HT-ELTFs. Each HT long training symbol is 4 μs. The number of space-time streams and the number of extension streams determines the number of HT-LTF symbols transmitted.

Tables² 19-12, 19-13 and 90-14 from IEEE Std 802.11-2012 are reproduced here.

NSTS Determination	NHTDLTF Determination	NHTELTF Determination
Table 19-12 defines the number of space-time streams (NSTS) based on the number of spatial streams (NSS) from the MCS and the STBC field.	Table 19-13 defines the number of HT-DLTFs required for the NSTS.	Table 19-14 defines the number of HT-ELTFs required for the number of extension spatial streams (NESS). NESS is defined in HT-SIG2.
NSS from MCS STBC field NSTS 1 0 1 1 1 2 2 0 2 2 1 3 2 2 4 3 0 3 3 1 4 4 0 4	NSTS NHTDLTF 1 1 2 2 3 4 4 4	NESS NHTELTF 0 0 1 1 2 2 3 4

Additional constraints include:

• N_HTLTF = N_HTDLTF + N_HTELTF ≤ 5.

• N_STS + N_ESS ≤ 4.

  • When N_STS = 3, N_ESS cannot exceed one.

  • If N_ESS = 1 when N_STS = 3 then N_HTLTF = 5.

Frequency Smoothing

Frequency smoothing can improve channel estimation by averaging out noise.

Frequency smoothing is recommended only for cases in which a single transmit antenna is used. Frequency smoothing consists of applying a moving-average filter that spans multiple adjacent subcarriers. Channel conditions dictate whether frequency smoothing is beneficial.

• If adjacent subcarriers are highly correlated, frequency smoothing results in significant noise reduction.

• In a highly frequency-selective channel, smoothing can degrade the quality of the channel estimate.

References

[1] IEEE Std 802.11™-2012 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.

[2] Perahia, E., and R. Stacey. Next Generation Wireless LANs: 802.11n and 802.11ac . 2nd Edition, United Kingdom: Cambridge University Press, 2013.

Extended Capabilities

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

Version History

Introduced in R2015b

R2023b: Single precision support

This function supports single-precision values for its numeric input arguments.