wlanTGnChannel

Filter signal through 802.11n multipath fading channel

Description

The wlanTGnChannel System object™ filters an input signal through an 802.11n™ (TGn) multipath fading channel.

The fading processing assumes the same parameters for all N_T-by-N_R links of the TGn channel. N_T is the number of transmit antennas and N_R is the number of receive antennas. Each link comprises all multipaths for that link.

To filter an input signal using a TGn multipath fading channel:

1. Create the wlanTGnChannel 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

tgn = wlanTGnChannel

tgn = wlanTGnChannel(Name,Value)

Description

tgn = wlanTGnChannel creates a TGn fading channel System object, tgn. This object filters a real or complex input signal through the TGn channel to obtain the channel-impaired signal.

tgn = wlanTGnChannel(Name,Value) creates a TGn channel object, tgn, and sets properties using one or more name-value pairs. Enclose each property name in quotes. For example, wlanTGnChannel('NumReceiveAntennas',2,'SampleRate',10e6) creates a TGn channel with two receive antennas and a 10 MHz sample rate.

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.

SampleRate — Sample rate of the input signal

20e6 (default) | positive scalar

Sample rate of the input signal in Hz, specified as a positive scalar.

Data Types: double

DelayProfile — Delay profile model

'Model-B' (default) | 'Model-A' | 'Model-C' | 'Model-D' | 'Model-E' | 'Model-F'

Delay profile model, specified as 'Model-A', 'Model-B', 'Model-C', 'Model-D', 'Model-E', or 'Model-F'.

The table summarizes the properties of the models.

Property	Model
	A	B	C	D	E	F
Breakpoint distance (m)	5	5	5	10	20	30
RMS delay spread (ns)	0	15	30	50	100	150
Maximum delay (ns)	0	80	200	390	730	1050
Rician K-factor (dB)	0	0	0	3	6	6
Number of taps	1	9	14	18	18	18
Number of clusters	1	2	2	3	4	6
Propagation scenario	Flat fading	Indoor residential	Indoor residential or small office	Office	Large office/warehouse	Large space indoor (pseudo-outdoor)

Data Types: char | string

CarrierFrequency — RF carrier frequency

5.25e9 (default) | positive scalar

RF carrier frequency in Hz, specified as a positive scalar.

Data Types: double

EnvironmentalSpeed — Speed of the scatterers

1.2 (default) | positive scalar

Speed of the scatterers in km/h, specified as a positive scalar.

Data Types: double

TransmitReceiveDistance — Distance between transmitter and receiver

3 (default) | positive scalar

Distance between the transmitter and receiver in meters, specified as a positive scalar.

TransmitReceiveDistance is used to compute the path loss, and to determine whether the channel has a line of sight (LOS) or non line of sight (NLOS) condition. The path loss and standard deviation of shadow fading loss depend on the separation between the transmitter and the receiver.

Data Types: double

NormalizePathGains — Normalize path gains

true or 1 (default) | false or 0

Normalize path gains, specified as a numeric or logical 1 (true) or 0 (false). To normalize the fading processes such that the total power of the path gains, averaged over time, is 0 dB, set this property to 1 (true). Otherwise, set this property to 0 (false).

Data Types: logical

NumTransmitAntennas — Number of transmit antennas

1 (default) | positive integer

Number of transmit antennas, specified as a positive integer.

Data Types: double

TransmitAntennaSpacing — Distance between transmit antenna elements

0.5 (default) | positive scalar

Distance between transmit antenna elements, specified as a positive scalar expressed in wavelengths.

TransmitAntennaSpacing supports uniform linear arrays only.

Dependencies

To enable this property, set the NumTransmitAntennas property to a value greater than 1.

Data Types: double

NumReceiveAntennas — Number of receive antennas

1 (default) | positive integer

Number of receive antennas, specified as a positive integer.

Data Types: double

ReceiveAntennaSpacing — Distance between receive antenna elements

0.5 (default) | positive scalar

Distance between receive antenna elements, specified as a positive scalar expressed in wavelengths.

ReceiveAntennaSpacing supports uniform linear arrays only.

Dependencies

To enable this property, set the NumReceiveAntennas property to a value greater than 1.

Data Types: double

LargeScaleFadingEffect — Large-scale fading effects

'None' (default) | 'Pathloss' | 'Shadowing' | 'Pathloss and shadowing'

Large-scale fading effects applied in the channel, specified as 'None', 'Pathloss', 'Shadowing', or 'Pathloss and shadowing'.

Data Types: char | string

FluorescentEffect — Fluorescent effect

true or 1 (default) | false or 0

Fluorescent effect, specified as a numeric or logical 1 (true) or 0 (false). To include Doppler effects from fluorescent lighting, set this property to 1 (true).

Dependencies

To enable this property, set the DelayProfile property to 'Model-D' or 'Model-E'.

Data Types: logical

PowerLineFrequency — Power line frequency

'60Hz' (default) | '50Hz'

Power line frequency in Hz, specified as '50Hz' or '60Hz'.

The power line frequency is 60 Hz in the United States and 50 Hz in Europe.

Dependencies

To enable this property, set the FluorescentEffect property to 1 (true) and the DelayProfile property to 'Model-D' or 'Model-E'.

Data Types: char | string

NormalizeChannelOutputs — Normalize channel outputs

true or 1 (default) | false or 0

Normalize channel outputs by the number of receive antennas, specified as a numeric or logical 1 (true) or 0 (false).

Data Types: logical

ChannelFiltering — Enable channel filtering

true or 1 (default) | false or 0

Enable channel filtering, specified as a numeric or logical 1 (true) or 0 (false). To enable channel filtering, set this property to 1 (true). To disable channel filtering, set this property to 0 (false)..

Note

If you set this property to 0 (false), the step object function does not accept an input signal. In this case, the NumSamples and SampleRate properties determine the duration of the fading process realization. The object acts as a source of path gains without filtering an input signal.

Data Types: logical

NumSamples — Number of time-domain samples

80 (default) | positive integer

Number of time-domain samples used to get path gain samples, specified as a positive integer.

Dependencies

To enable this property, set the ChannelFiltering property to false.

Data Types: double

OutputDataType — Data type of impaired signal

'double' (default) | 'single'

Data type of impaired signal, specified as one of these values:

• 'double' – Return the pathGains output as a double-precision matrix

• 'single' – Return the pathGains output as a single-precision matrix

Dependencies

To enable this property, set the ChannelFiltering property to 0 (false).

Data Types: char | string

RandomStream — Source of random number stream

'Global stream' (default) | 'mt19937ar with seed'

Source of random number stream, specified as 'Global stream' or 'mt19937ar with seed'.

If you set this property to 'Global stream', the System object uses the current global random number stream to generate random numbers. In this case, the reset function resets the filters and creates a new channel realization.

If you set this property to 'mt19937ar with seed', the mt19937ar algorithm generates random numbers. In this case, the reset function not only resets the filters, but also reinitializes the random number stream to the value of the Seed property. This results in the same channel realization.

Note

The random numbers of the channel components are distributed as follows:

• The random phase of the Doppler component due to fluorescent lights is uniformly distributed. See equation 27 of TGn Channel Models for more information.

• In multi-user scenarios using the TGac, TGah, or TGax channel models, the per-user angle-of-arrival (AoA) and angle-of-departure (AoD) rotations discussed in the MIMO Enhancements section are uniformly distributed.

• The fading samples are generated by a normally-distributed complex uncorrelated Gaussian process with zero mean and unit variance in discrete time.

Data Types: char | string

Seed — Initial seed of mt19937ar random number stream

73 (default) | nonnegative integer

Initial seed of an mt19937ar random number stream, specified as a nonnegative integer. The Seed property reinitializes the mt19937ar random number stream in the reset function.

Dependencies

To enable this property, set the RandomStream property to 'mt19937ar with seed'.

Data Types: double

PathGainsOutputPort — Enable path gain output

false or 0 (default) | true or 1

Enable path gain output computation, specified as a numeric or logical 1 (true) or 0 (false).

Data Types: logical

Usage

Syntax

y = tgn(x)

[y,pathGains] = tgn(x)

pathGains = tgac(x)

Description

y = tgn(x) filters input signal x through the TGn fading channel defined by the wlanTGnChannel System object, tgn, and returns the result in y.

[y,pathGains] = tgn(x) also returns in pathGains the TGn channel path gains of the underlying fading process.

This syntax applies when you set the PathGainsOutputPort property to 1 (true).

pathGains = tgac(x) returns the path gains. The NumSamples property determines the duration of the fading process.

This syntax applies when you set the ChannelFiltering property to 0 (false).

Input Arguments

x — Input signal

complex matrix

Input signal, specified as a real or complex N_S-by-N_T matrix, where:

• N_S is the number of samples.

• N_T is the number of transmit antennas and must be equal to the NumTransmitAntennas property value.

Data Types: single | double
Complex Number Support: Yes

Output Arguments

y — Output signal

complex matrix

Output signal, returned as an N_S-by-N_R complex matrix, where:

• N_S is the number of samples.

• N_R is the number of receive antennas and is equal to the NumReceiveAntennas property value.

Data Types: single | double

pathGains — Path gains of the fading process

complex array

Path gains of the fading process, returned as an N_S-by-N_P-by-N_T-by-N_R complex array, where:

• N_S is the number of samples.

• N_P is the number of resolvable paths, that is, the number of paths defined for the case specified by the DelayProfile property.

• N_T is the number of transmit antennas and is equal to the NumTransmitAntennas property value.

• N_R is the number of receive antennas and is equal to the NumReceiveAntennas property value.

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 wlanTGnChannel

info	Characteristic information about multipath fading channels

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

Note

reset: If the RandomStream property of the System object is set to 'Global stream', the reset function resets the filters only. If you set RandomStream to 'mt19937ar with seed', the reset function not only resets the filters, but also reinitializes the random number stream to the value of the Seed property. This results in the same channel realization.

Examples

Transmit HT Waveform Through TGn Channel

Generate an HT waveform and pass it through a TGn SISO channel. Display the spectrum of the resultant signal.

Set the channel bandwidth and the corresponding sample rate.

bw = 'CBW40';
fs = 40e6;

Generate an HT waveform for a 40 MHz channel.

cfg = wlanHTConfig('ChannelBandwidth',bw);
txSig = wlanWaveformGenerator(randi([0 1],1000,1),cfg);

Create a TGn SISO channel with path loss and shadowing enabled.

tgnChan = wlanTGnChannel('SampleRate',fs, ...
    'LargeScaleFadingEffect','Pathloss and shadowing');

Pass the HT waveform through the channel.

rxSig = tgnChan(txSig);

Plot the spectrum of the received waveform.

saScope = spectrumAnalyzer(SampleRate=fs,YLimits=[-120 -40]);
saScope(rxSig)

Because path loss and shadowing are enabled, the mean received power across the spectrum is approximately -60 dBm.

Transmit HT Waveform Through 4x2 MIMO Channel

Create an HT waveform having four transmit antennas and two space-time streams.

cfg = wlanHTConfig('NumTransmitAntennas',4,'NumSpaceTimeStreams',2, ...
    'SpatialMapping','Fourier');
txSig = wlanWaveformGenerator([1;0;0;1],cfg);

Create a 4x2 MIMO TGn channel and disable large-scale fading effects.

tgnChan = wlanTGnChannel('SampleRate',20e6, ...
    'NumTransmitAntennas',4, ...
    'NumReceiveAntennas',2, ...
    'LargeScaleFadingEffect','None');

Pass the transmit waveform through the channel.

rxSig = tgnChan(txSig);

Display the spectrum of the two received space-time streams.

saScope = spectrumAnalyzer(SampleRate=20e6, ...
    ShowLegend=true, ...
    ChannelNames={'Stream 1','Stream 2'});
saScope(rxSig)

Recover HT Data from 2x2 MIMO Channel

Transmit an HT-LTF and an HT data field through a noisy 2x2 MIMO channel. Demodulate the received HT-LTF to estimate the channel coefficients. Recover the HT data and determine the number of bit errors.

Set the channel bandwidth and corresponding sample rate.

bw = 'CBW40';
fs = 40e6;

Create HT-LTF and HT data fields having two transmit antennas and two space-time streams.

cfg = wlanHTConfig('ChannelBandwidth',bw, ...
    'NumTransmitAntennas',2,'NumSpaceTimeStreams',2);
txPSDU = randi([0 1],8*cfg.PSDULength,1);
txLTF = wlanHTLTF(cfg);
txDataSig = wlanHTData(txPSDU,cfg);

Create a 2x2 MIMO TGn channel with path loss and shadowing enabled.

tgnChan = wlanTGnChannel('SampleRate',fs, ...
    'NumTransmitAntennas',2,'NumReceiveAntennas',2, ...
    'LargeScaleFadingEffect','None');

Create AWGN channel noise, setting SNR = 15 dB.

chNoise = comm.AWGNChannel('NoiseMethod','Signal to noise ratio (SNR)',...
    'SNR',15);

Pass the signals through the TGn channel and noise models.

rxLTF = chNoise(tgnChan(txLTF));
rxDataSig = chNoise(tgnChan(txDataSig));

Create an AWGN channel for a 40 MHz channel with a 9 dB noise figure. The noise variance, nVar, is equal to kTBF, where k is Boltzmann's constant, T is the ambient temperature of 290 K, B is the bandwidth (sample rate), and F is the receiver noise figure.

nVar = 10^((-228.6 + 10*log10(290) + 10*log10(fs) + 9)/10);
awgnChan = comm.AWGNChannel('NoiseMethod','Variance','Variance',nVar);

Pass the signals through the channel.

rxLTF = awgnChan(rxLTF);
rxDataSig = awgnChan(rxDataSig);

Demodulate the HT-LTF. Use the demodulated signal to estimate the channel coefficients.

dLTF = wlanHTLTFDemodulate(rxLTF,cfg);
chEst = wlanHTLTFChannelEstimate(dLTF,cfg);

Recover the data and determine the number of bit errors.

rxPSDU = wlanHTDataRecover(rxDataSig,chEst,nVar,cfg);
numErr = biterr(txPSDU,rxPSDU)

numErr = 
0

Compare Random Number Sources for TGn Channel

Create a non-HT configuration object with default parameters. Generate a waveform for the configuration.

cfg = wlanNonHTConfig;
tx = wlanWaveformGenerator([1;0;0;1],cfg);

Create a TGn channel System object with default parameters. Display the value of the RandomStream property.

tgnChan = wlanTGnChannel;
disp(tgnChan.RandomStream)

Global stream

Pass the waveform through the channel twice, resetting the System object between the two iterations.

for i = 1:2
    rx(:,i) = tgnChan(tx);
    reset(tgnChan);
end

Compare the two received waveforms. They are different because the reset object function resets the filters and the channel object takes new random numbers from the global stream. This causes it to generate a different channel realization.

isequal(rx(:,1),rx(:,2))

ans = logical
   0

Now release the System object and set the RandomStream property to "mt19937ar with seed".

release(tgnChan);
tgnChan.RandomStream = "mt19937ar with seed";

Pass the waveform through the channel twice, resetting the System object between the two iterations.

for i = 1:2
    rx(:,i) = tgnChan(tx);
    reset(tgnChan);
end

Compare the two received waveforms. They are equal because the channel realization is the same for both iterations. This happens because the reset function reinitializes the random number stream to the value of the Seed property, so the channel object uses the same random numbers for both channel realizations.

isequal(rx(:,1),rx(:,2))

ans = logical
   1

Algorithms

The 802.11n channel object uses a filtered Gaussian noise model in which the path delays, powers, angular spread, angles of arrival, and angles of departure are determined empirically. The specific modeling approach is described in [1].

Multipath Parameters

The channel is modeled as several clusters, each of which represents an independent propagation path between the transmitter and the receiver. A cluster is composed of subpaths, or taps, which share angular spreads, angles of arrival, and angles of departure. Delay and power level vary from tap to tap. Within the TGn model, clusters comprise 1–7 taps. The cluster parameters for cluster 1 of model B are shown in the table.

Parameter	Tap
	1	2	3	4	5
Delay (ns)	0	10	20	30	40
Power (dB)	0	–5.4	–10.8	–16.2	–21.7
Angle of arrival (°)	4.3	4.3	4.3	4.3	4.3
Receiver angular spread (°)	14.4	14.4	14.4	14.4	14.4
Angle of departure (°)	225.1	225.1	225.1	225.1	225.1
Transmitter angular spread (°)	14.4	14.4	14.4	14.4	14.4

For each model, the first tap has a line of sight (LOS) between the transmitter and receiver, whereas all other taps are non line of sight (NLOS). As a result, the first tap exhibits Rician behavior, while the others exhibit Rayleigh behavior. The Rician K-factor is the ratio between the power in the first tap and the power in the other taps. A large K-factor indicates a strong LOS component.

The angles of arrival and departure for each cluster are randomly selected from a uniform distribution over [0, 2π]. These angles are independent of each other and are fixed for all channel realizations. By fixing the values, the transmit and receive correlation matrices are computed only once. Angular spread values were indirectly determined from empirical data and fall within the 20° to 40° range.

Path Loss and Shadowing

The path loss exponent and the standard deviation of the shadow fading loss characterize each model. The two parameters depend on the presence of a LOS between the transmitter and receiver. For paths with a transmitter-to-receiver distance, d, less that the breakpoint distance, d_BP, the LOS parameters apply. For d >d_BP, the NLOS parameters apply. The table summarizes the path loss and shadow fading parameters.

Parameter	Model
	A	B	C	D	E	F
Breakpoint distance, dBP (m)	5	5	5	10	20	30
Path loss exponent for d ≤ dBP	2	2	2	2	2	2
Path loss exponent for d >dBP	3.5	3.5	3.5	3.5	3.5	3.5
Shadow fading σ (dB) for d ≤ dBP	3	3	3	3	3	3
Shadow fading σ (dB) for d >dBP	4	4	5	5	6	6

Doppler Effects

In indoor environments, the transmitter and receiver are stationary, and Doppler effects arise from people moving between them. The TGn model employs a bell-shaped Doppler spectrum in which the environmental speed, ν₀, is 1.2 km/h by default (it is specified by the EnvironmentalSpeed property). The Doppler spread, f_d, is calculated as f_d = ν₀/λ, where λ is the carrier wavelength.

The channel sampling rate, F_s, must be lower than the input sampling rate to avoid aliasing. It is calculated as:

F_s= (ν₀×F_c)/(300×c)

where F_c is the carrier frequency, specified by the CarrierFrequency property, c is the speed of light and ν₀ is defined in m/s.

In addition to basic Doppler effects resulting from environmental motion, fluorescent lights introduce signal fading at twice the power line frequency. The effects show up as frequency-selective amplitude modulation. Again, to avoid aliasing, the Nyquist frequency of the first interpolation factor must be greater than the highest harmonic.

The effect is included in models D and E. To disable this effect, set the FluorescentEffect property to false.

References

[1] Erceg, V., L. Schumacher, P. Kyritsi, et al. TGn Channel Models. Version 4. IEEE 802.11-03/940r4, May 2004.

[2] Kermoal, J. P., L. Schumacher, K. I. Pedersen, P. E. Mogensen, and F. Frederiksen, “A Stochastic MIMO Radio Channel Model with Experimental Validation”. IEEE Journal on Selected Areas in Communications., Vol. 20, No. 6, August 2002, pp. 1211–1226.

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 R2015b