wlanTGacChannel
Filter signal through 802.11ac multipath fading channel
Description
The wlanTGacChannel
System object™ filters an input signal through an 802.11ac™ (TGac) multipath fading channel.
The fading processing assumes the same parameters for all NT-by-NR links of the TGac channel, where NT is the number of transmit antennas and NR is the number of receive antennas. Each link comprises all multipaths for that link.
To filter an input signal using a TGac multipath fading channel:
Create the
wlanTGacChannel
object and set its properties.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
Description
creates a TGac fading
channel System object, tgac
= wlanTGacChanneltgac
. This object filters a real or complex input
signal through the TGac channel to obtain the channel-impaired signal.
creates a TGac channel object, tgac
= wlanTGacChannel(Name
,Value
)tgac
, and sets properties using one or
more name-value pairs. Enclose each property name in quotes. For example,
wlanTGacChannel('NumReceiveAntennas',2,'SampleRate',10e6)
creates a
TGac 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
80e6
(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'
. To enable the FluorescentEffect
property, select either 'Model-D'
or
'Model-E'
.
The table summarizes the properties of the models before the bandwidth reduction factor. For more information, see Increased Bandwidth.
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) |
The number of clusters represents the number of independently modeled propagation paths.
Data Types: char
| string
ChannelBandwidth
— Channel bandwidth
'CBW80'
(default) | 'CBW20'
| 'CBW40'
| 'CBW160'
Channel bandwidth, specified as 'CBW20'
,
'CBW40'
, 'CBW80'
, or
'CBW160'
. The default is 'CBW80'
, which
corresponds to an 80 MHz channel bandwidth.
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
0.089
(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
UserIndex
— User index for single or multi-user scenario
0
(default) | positive integer
User index, specified as a nonnegative integer. If the property is set to
0
, the angles of arrival and departure from the TGn channel model
are used in the calculation of the spatial correlation matrix. If the property is set to
a positive integer, pseudorandom offsets are applied to the TGn angles of arrival and
departure before the calculation of the spatial correlation matrix. For more details,
see the section on MIMO Enhancements.
Data Types: double
TransmissionDirection
— Transmission direction
'Downlink'
(default) | 'Uplink'
Transmission direction of the active link, specified as either
'Downlink'
or 'Uplink'
.The default value,
'Downlink'
, specifies transmission from an access point to a user
station.
Data Types: char
| string
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
320
(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 0
(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 thepathGains
output as a double-precision matrix'single'
– Return thepathGains
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
Description
[
also returns in y
,pathGains
] = tgac(x
)pathGains
the TGac channel path gains of the
underlying fading process.
This syntax applies when you set the PathGainsOutputPort
property to 1
(true
).
Input Arguments
x
— Input signal
complex matrix
Input signal, specified as a real or complex NS-by-NT matrix, where:
NS is the number of samples.
NT 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 NS-by-NR complex matrix, where:
NS is the number of samples.
NR 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 NS-by-NP-by-NT-by-NR complex array, where:
NS is the number of samples.
NP is the number of resolvable paths, that is, the number of paths defined for the case specified by the
DelayProfile
property.NT is the number of transmit antennas and is equal to the
NumTransmitAntennas
property value.NR 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)
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 VHT Waveform Through TGac Channel
Generate a VHT waveform and pass it through a TGac SISO channel. Display the spectrum of the resultant signal.
Set the channel bandwidth and the corresponding sample rate.
bw = 'CBW80';
fs = 80e6;
Generate a VHT waveform.
cfg = wlanVHTConfig; txSig = wlanWaveformGenerator(randi([0 1],1000,1),cfg);
Create a TGac SISO channel with path loss and shadowing enabled.
tgacChan = wlanTGacChannel('SampleRate',fs,'ChannelBandwidth',bw, ... 'LargeScaleFadingEffect','Pathloss and shadowing');
Pass the VHT waveform through the channel.
rxSig = tgacChan(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 VHT Waveform Through 4x2 MIMO Channel
Create a VHT waveform with four transmit antennas and two space-time streams.
cfg = wlanVHTConfig('NumTransmitAntennas',4,'NumSpaceTimeStreams',2, ... 'SpatialMapping','Fourier'); txSig = wlanWaveformGenerator([1;0;0;1],cfg);
Create a 4x2 MIMO TGac channel and disable large-scale fading effects.
tgacChan = wlanTGacChannel('SampleRate',80e6,'ChannelBandwidth','CBW80', ... 'NumTransmitAntennas',4,'NumReceiveAntennas',2, ... 'LargeScaleFadingEffect','None');
Pass the transmit waveform through the channel.
rxSig = tgacChan(txSig);
Display the spectrum of the two received space-time streams.
saScope = spectrumAnalyzer(SampleRate=80e6, ... ShowLegend=true, ... ChannelNames={'Stream 1','Stream 2'}); saScope(rxSig)
Recover VHT Data from 2x2 MIMO Channel
Transmit a VHT-LTF and a VHT data field through a noisy 2x2 MIMO channel. Demodulate the received VHT-LTF to estimate the channel coefficients. Recover the VHT data and determine the number of bit errors.
Set the channel bandwidth and corresponding sample rate.
bw = 'CBW160';
fs = 160e6;
Create VHT-LTF and VHT data fields with two transmit antennas and two space-time streams.
cfg = wlanVHTConfig('ChannelBandwidth',bw, ... 'NumTransmitAntennas',2,'NumSpaceTimeStreams',2); txPSDU = randi([0 1],8*cfg.PSDULength,1); txLTF = wlanVHTLTF(cfg); txDataSig = wlanVHTData(txPSDU,cfg);
Create a 2x2 MIMO TGac channel.
tgacChan = wlanTGacChannel('SampleRate',fs,'ChannelBandwidth',bw, ... 'NumTransmitAntennas',2,'NumReceiveAntennas',2);
Create AWGN channel noise, setting the SNR to 15 dB.
chNoise = comm.AWGNChannel('NoiseMethod','Signal to noise ratio (SNR)',... 'SNR',15);
Pass the signals through the TGac channel and noise models.
rxLTF = chNoise(tgacChan(txLTF)); rxDataSig = chNoise(tgacChan(txDataSig));
Create an AWGN channel for a 160 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); rxNoise = comm.AWGNChannel('NoiseMethod','Variance','Variance',nVar);
Pass the signals through the receiver noise model.
rxLTF = rxNoise(rxLTF); rxDataSig = rxNoise(rxDataSig);
Demodulate the VHT-LTF. Use the demodulated signal to estimate the channel coefficients.
dLTF = wlanVHTLTFDemodulate(rxLTF,cfg); chEst = wlanVHTLTFChannelEstimate(dLTF,cfg);
Recover the data and determine the number of bit errors.
rxPSDU = wlanVHTDataRecover(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 algorithms used to model the TGac channel are based on those used for the TGn channel
and are described in wlanTGnChannel
and [1]. The changes to support the TGac
channel include:
Increased bandwidth
Higher-order MIMO
Multi-user MIMO
Reduced Doppler
Complete information on the changes required to support TGac channels can be found in [2].
Increased Bandwidth
TGac channels support bandwidths of up to 160 MHz, whereas TGn channels have a maximum bandwidth of 40 MHz. By increasing the sampling rate and decreasing the tap spacing of the power delay profile (PDP), the TGn model is used as the basis for TGac. The channel sampling rate is increased by a factor of , where W is the bandwidth. The PDP tap spacing is reduced by the same factor. This is shown in the table, which is adapted from Table 1 in [2].
Bandwidth, W | Sampling Rate Expansion Factor | PDP Tap Spacing (ns) |
---|---|---|
W ≤ 40 MHz | 1 | 10 |
40 MHz < W ≤ 80 MHz | 2 | 5 |
80 MHz < W ≤ 160 MHz | 4 | 2.5 |
160 MHz < W ≤ 320 MHz | 8 | 1.25 |
320 MHz < W ≤ 640 MHz | 16 | 0.625 |
640 MHz < W ≤ 1280 MHz | 32 | 0.3125 |
MIMO Enhancements
The TGn channel model supports no more than 4x4 MIMO, while the TGac model supports 8x8 MIMO.
The TGac model uses per-user angle diversity to support simultaneous communication
between multiple user stations and an access point. For each channel realization, the model
achieves this by adding pseudorandom offsets to the angles of arrival and departure of each
cluster before the calculation of the spatial correlation matrix. Different offsets are
chosen for each positive value of the UserIndex
property. This causes
the angles of arrival and departure for each cluster to differ between users.
Changing the TransmissionDirection
property swaps the angle of
arrival of each cluster with its corresponding angle of departure. For more details, see the
Appendix of [2].
To see how the UserIndex
property can be used in an application,
see this example: 802.11ax Packet Error Rate Simulation for Uplink Trigger-Based Format.
Reduced Doppler
Indoor channel measurements indicate that the magnitude of Doppler assumed in the TGn channel model is too high for stationary users. As such, the TGac channel model uses a reduced environment velocity of 0.089 km/hr. This model assumes a coherence time of 800 ms or, equivalently, an RMS Doppler spread of 0.4 Hz for a 5 GHz carrier frequency.
References
[1] Erceg, V., L. Schumacher, P. Kyritsi, et al. TGn Channel Models. Version 4. IEEE 802.11-03/940r4, May 2004.
[2] Breit, G., H. Sampath, S. Vermani, et al.TGac Channel Model Addendum. Version 12. IEEE 802.11-09/0308r12, March 2010.
[3] 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 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
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