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Construct Rician fading channel object

`chan = ricianchan(ts,fd,k)`

chan = ricianchan(ts,fd,k,tau,pdb)

chan = ricianchan(ts,fd,k,tau,pdb,fdLOS)

chan = ricianchan

`chan = ricianchan(ts,fd,k)`

constructs
a frequency-flat (single path) Rician fading-channel object. `ts`

is
the sample time of the input signal, in seconds. `fd`

is
the maximum Doppler shift, in hertz. `k`

is the Rician
K-factor in linear scale. You can model the effect of the channel `chan`

on
a signal `x`

by using the syntax `y = filter(chan,x)`

.
See `filter`

for more information.

`chan = ricianchan(ts,fd,k,tau,pdb)`

constructs
a frequency-selective (multiple paths) fading-channel object. If `k`

is
a scalar, then the first discrete path is a Rician fading process
(it contains a line-of-sight component) with a K-factor of `k`

,
while the remaining discrete paths are independent Rayleigh fading
processes (no line-of-sight component). If `k`

is
a vector of the same size as `tau`

, then each discrete
path is a Rician fading process with a K-factor given by the corresponding
element of the vector `k`

. `tau`

is
a vector of path delays, each specified in seconds. `pdb`

is
a vector of average path gains, each specified in dB.

`chan = ricianchan(ts,fd,k,tau,pdb,fdLOS)`

specifies `fdlos`

as
the Doppler shift(s) of the line-of-sight component(s) of the discrete
path(s), in hertz. `fdlos`

must be the same size
as `k`

. If `k`

and `fdlos`

are
scalars, the line-of-sight component of the first discrete path has
a Doppler shift of `fdlos`

, while the remaining discrete
paths are independent Rayleigh fading processes. If `fdlos`

is
a vector of the same size as `k`

, the line-of-sight
component of each discrete path has a Doppler shift given by the corresponding
element of the vector `fdlos`

. By default, `fdlos`

is `0`

.
The initial phase(s) of the line-of-sight component(s) can be set
through the property `DirectPathInitPhase`

.

`chan = ricianchan`

sets
the maximum Doppler shift to `0`

, the Rician K-factor
to `1`

, and the Doppler shift and initial phase of
the line-of-sight component to `0`

. This syntax models
a static frequency-flat channel, and, in this trivial case, the sample
time of the signal is unimportant.

The following tables describe the properties of the channel
object, `chan`

, that you can set and that MATLAB^{®} technical
computing software sets automatically. To learn how to view or change
the values of a channel object, see Displaying and Changing Object Properties.

**Writeable Properties**

Property | Description |
---|---|

`InputSamplePeriod` | Sample period of the signal on which the channel acts, measured in seconds. |

`DopplerSpectrum` | Doppler spectrum object(s). The default is a Jakes doppler object. |

`MaxDopplerShift` | Maximum Doppler shift of the channel, in hertz (applies to all paths of a channel). |

`KFactor` | Rician K-factor (scalar or vector). The default value is 1 (line-of-sight component on the first path only). |

`PathDelays` | Vector listing the delays of the discrete paths, in seconds. |

`AvgPathGaindB` | Vector listing the average gain of the discrete paths, in decibels. |

`DirectPathDopplerShift` | Doppler shift(s) of the line-of-sight component(s) in hertz. The default value is 0. |

`DirectPathInitPhase` | Initial phase(s) of line-of-sight component(s) in radians. The default value is 0. |

`NormalizePathGains` | If this value is `1` ,
the Rayleigh fading process is normalized such that the expected value
of the path gains' total power is 1. |

`StoreHistory` | If this value is `1` ,
channel state information needed by the channel visualization tool
is stored as the channel filter function processes the signal. The
default value is `0` . |

`StorePathGains` | If this value is `1` ,
the complex path gain vector is stored as the channel filter function
processes the signal. The default value is `0` . |

`ResetBeforeFiltering` | If this value is `1` ,
each call to `filter` resets the state of `chan` before
filtering. If it is `0` , the fading process maintains
continuity from one call to the next. |

**Read-Only Properties**

Property | Description | When MATLAB Sets or Updates Value |
---|---|---|

`ChannelType` | Fixed value, .`'Rician'` | When you create object. |

`PathGains` | Complex vector listing the
current gains of the discrete paths. When you create or reset `chan` , `PathGains` is
a random vector influenced by `AvgPathGaindB` and `NormalizePathGains` . | When you create object, reset object, or use it to filter a signal. |

`ChannelFilterDelay` | Delay of the channel filter,
measured in samples. The ChannelFilterDelay property returns a delay value that is valid only if the first value of the PathGain is the biggest path gain. In other words, main channel energy is in the first path. | When you create object or
change ratio of `InputSamplePeriod` to `PathDelays` . |

`NumSamplesProcessed` | Number of samples the channel
processed since the last reset. When you create or reset `chan` ,
this property value is `0` . | When you create object, reset object, or use it to filter a signal. |

Changing the length of `PathDelays`

also changes
the length of `AvgPathGaindB`

, the length of `KFactor`

if `KFactor`

is
a vector (no change if it is a scalar), and the length of `DopplerSpectrum`

if `DopplerSpectrum`

is
a vector (no change if it is a single object).

`DirectPathDopplerShift`

and `DirectPathInitPhase`

both
follow changes in `KFactor`

.

The `PathDelays`

and `AvgPathGaindB`

properties
of the channel object must always have the same vector length, because
this length equals the number of discrete paths of the channel. The `DopplerSpectrum`

property
must either be a single Doppler object or a vector of Doppler objects
with the same length as `PathDelays`

.

If you change the length of `PathDelays`

, MATLAB truncates
or zero-pads the value of `AvgPathGaindB`

if necessary
to adjust its vector length (MATLAB may also change the values
of read-only properties such as `PathGains`

and `ChannelFilterDelay`

).
If `DopplerSpectrum`

is a vector of Doppler objects,
and you increase or decrease the length of `PathDelays`

, MATLAB will
add Jakes Doppler objects or remove elements from `DopplerSpectrum`

,
respectively, to make it the same length as `PathDelays`

.

If `StoreHistory`

is set to `1`

(the
default is `0`

), the object stores channel state
information as the channel filter function processes the signal.
You can then visualize this state information through a GUI using
the `plot (channel)`

method.

Setting `StoreHistory`

to `1`

will
result in a slower simulation. If you do not want to visualize channel
state information using `plot (channel)`

,
but want to access the complex path gains, then set `StorePathGains`

to `1`

,
while keeping `StoreHistory`

as `0`

.

If `MaxDopplerShift`

is set to `0`

(the
default), the channel object, `chan`

, models a static
channel.

Use the syntax `reset(chan)`

to generate a
new channel realization.

The methodology used to simulate fading channels is described
in Methodology for Simulating SISO Multipath Fading Channels,
where the properties specific to the Rician channel object are related
to the quantities of this section as follows (see the `rayleighchan`

reference page for properties
common to both Rayleigh and Rician channel objects):

The

`Kfactor`

property contains the value of $${K}_{r}$$ (if it’s a scalar) or $$\left\{{K}_{r,k}\right\}$$, $$1\le k\le K$$ (if it’s a vector).The

`DirectPathDopplerShift`

property contains the value of $${f}_{d,LOS}$$ (if it’s a scalar) or $$\left\{{f}_{d,LOS,k}\right\}$$, $$1\le k\le K$$ (if it’s a vector).The

`DirectPathInitPhase`

property contains the value of $${\theta}_{LOS}$$ (if it’s a scalar) or $$\left\{{\theta}_{LOS,k}\right\}$$, $$1\le k\le K$$ (if it’s a vector).

The characteristics of a channel can be plotted using the channel visualization tool. You can use the channel visualization tool in Normal mode and Accelerator mode. For more information, see Channel Visualization.

The example in Quasi-Static Channel Modeling uses this function.

[1] Jeruchim, M., Balaban, P., and Shanmugan,
K., *Simulation of Communication Systems*, Second
Edition, New York, Kluwer Academic/Plenum, 2000.

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