(Removed) Construct bi-Gaussian Doppler spectrum object
doppler.bigaussian has been removed. Use doppler('BiGaussian',...) instead.
dop = doppler.bigaussian(property1,value1,...)
dop = doppler.bigaussian
The doppler.bigaussian function creates a bi-Gaussian Doppler
spectrum object to be used for the DopplerSpectrum property of a
channel object (created with either the rayleighchan function or
the ricianchan
function).
dop = doppler.bigaussian(property1,value1,...)
creates a bi-Gaussian Doppler spectrum object with properties as specified by the
property/value pairs. If you do not specify a value for a property, the property is
assigned a default value.
dop = doppler.bigaussian creates a bi-Gaussian
Doppler spectrum object with default properties. The constructed Doppler spectrum object
is equivalent to a single Gaussian Doppler spectrum centered at zero frequency. The
equivalent command with property/value pairs is:
dop = doppler.bigaussian('SigmaGaussian1', 1/sqrt(2), ...
'SigmaGaussian2', 1/sqrt(2), ...
'CenterFreqGaussian1', 0, ...
'CenterFreqGaussian2', 0, ...
'GainGaussian1', 0.5, ...
'GainGaussian2', 0.5)The bi-Gaussian Doppler spectrum object contains the following properties.
| Property | Description |
|---|---|
SpectrumType | Fixed value, 'BiGaussian' |
SigmaGaussian1 | Normalized standard deviation of first Gaussian function (real positive finite scalar value) |
SigmaGaussian2 | Normalized standard deviation of second Gaussian function (real positive finite scalar value) |
CenterFreqGaussian1 | Normalized center frequency of first Gaussian function (real scalar value between -1 and 1) |
CenterFreqGaussian2 | Normalized center frequency of second Gaussian function (real scalar value between -1 and 1) |
GainGaussian1 | Power gain of first Gaussian function (linear scale, real nonnegative finite scalar value) |
GainGaussian2 | Power gain of second Gaussian function (linear scale, real nonnegative finite scalar value) |
All properties are writable except for the SpectrumType
property.
The properties SigmaGaussian1, SigmaGaussian2,
GainGaussian1, and GainGaussian2 are
normalized by the MaxDopplerShift property of the associated channel
object.
Analytically, the normalized standard deviations of the first and second Gaussian
functions are determined as and , respectively, where and are the standard deviations of the first and second Gaussian
functions, and is the maximum Doppler shift, in hertz. Similarly, the normalized
center frequencies of the first and second Gaussian functions are determined as and , respectively, where and are the center frequencies of the first and second Gaussian functions.
The properties GainGaussian1 and GainGaussian2
correspond to the power gains and , respectively, of the two Gaussian functions.
The bi-Gaussian power spectrum consists of two frequency-shifted Gaussian spectra. The COST207 channel models ([1], [2], [3]) specify two distinct bi-Gaussian Doppler spectra, GAUS1 and GAUS2, to be used in modeling long echos for urban and hilly terrain profiles.
The normalized bi-Gaussian Doppler spectrum is given analytically by:
where and are standard deviations, and are center frequencies, and are power gains, and is a normalization coefficient.
If either or , a frequency-shifted Gaussian Doppler spectrum is obtained.
The following MATLAB code first creates a bi-Gaussian Doppler spectrum object with the
same parameters as that of a COST 207 GAUS2 Doppler spectrum. It then creates a Rayleigh
channel object with a maximum Doppler shift of and assigns the constructed Doppler spectrum object to its
DopplerSpectrum property.
dop_bigaussian = doppler.bigaussian(‘SigmaGaussian1’, 0.1, ... ‘SigmaGaussian2’, 0.15, ‘CenterFreqGaussian1’, 0.7, ... ‘CenterFreqGaussian2’, -0.4, ‘GainGaussian1’, 1, ... ‘GainGaussian2’, 1/10^1.5) chan = rayleighchan(1e-3, 30); chan.DopplerSpectrum = dop_bigaussian;
[1] COST 207 WG1, Proposal on channel transfer functions to be used in GSM tests late 1986, COST 207 TD (86) 51 Rev. 3, Sept. 1986.
[2] COST 207, Digital land mobile radio communications, Office for Official Publications of the European Communities, Final report, Luxembourg, 1989.
[3] Pätzold, M., Mobile Fading Channels, Wiley, 2002.