Mobile Communications/Non-Frequency-Selective Fading With Direct Component: Difference between revisions

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{{Header
{{Header
|Untermenü=Time variant transmission channels
|Untermenü=Time-Variant Transmission Channels
|Vorherige Seite=Statistical bonds within the Rayleigh process
|Vorherige Seite=Statistical Bonds Within the Rayleigh Process
|Nächste Seite=General description of time variant systems
|Nächste Seite=General description of time variant systems
}}
}}
 
== Channel model and Rice PDF ==
== Kanalmodell und Rice–WDF ==
<br>
<br>
Die&nbsp; [[Mobile_Kommunikation/Wahrscheinlichkeitsdichte_des_Rayleigh%E2%80%93Fadings#Allgemeine_Beschreibung_des_Mobilfunkkanals| Rayleigh&ndash;Verteilung]]&nbsp; beschreibt den Mobilfunkkanal unter der Annahme, dass kein direkter Pfad vorhanden ist und sich somit der multiplikative Faktor&nbsp; $z(t) = x(t) + {\rm j} \cdot y(t)$&nbsp; allein aus diffus gestreuten Komponenten zusammensetzt.  
The&nbsp; [[Mobile_Communications/Probability_Density_of_Rayleigh_Fading#Modeling_of_non-frequency_selective_fading| $\text{Rayleigh distribution}$]]&nbsp; describes the mobile communication channel under the assumption that there is no direct path and thus the multiplicative factor&nbsp; $z(t) = x(t) + {\rm j} \cdot y(t)$&nbsp; is solely composed of diffusely scattered components.  


[[File:EN_Mob_T_1_4_S1.png|right|frame|Rice-Fading-Kanalmodell|class=fit]]
If a direct component&nbsp; $($Line of Sight,&nbsp; $\rm LoS)$&nbsp; is present, it is necessary to add direct components &nbsp; $x_0$&nbsp; and/or&nbsp; $y_0$&nbsp; to the zero mean Gaussian processes &nbsp; $x(t)$&nbsp; and&nbsp; $y(t)$:
 
[[File:EN_Mob_T_1_4_S1.png|right|frame|Rice fading channel model|class=fit]]
Bei Vorhandensein einer Direktkomponente&nbsp; $($englisch:&nbsp; <i>Line of Sight</i>,&nbsp; $\rm LoS)$&nbsp; muss man im Modell zu den mittelwertfreien Gaußprozessen&nbsp; $x(t)$&nbsp; und&nbsp; $y(t)$&nbsp; noch Gleichkomponenten&nbsp; $x_0$&nbsp; und/oder&nbsp; $y_0$&nbsp; hinzufügen:


::<math>x(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} x(t) +x_0 \hspace{0.05cm}, \hspace{0.2cm} y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} y(t) +y_0\hspace{0.05cm},</math>
::<math>x(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} x(t) +x_0 \hspace{0.05cm}, \hspace{0.2cm} y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} y(t) +y_0\hspace{0.05cm},</math>
Line 18: Line 16:
::<math>z(t) = x(t) + {\rm j} \cdot y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} z(t) +z_0 \hspace{0.05cm},\hspace{0.2cm}
::<math>z(t) = x(t) + {\rm j} \cdot y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} z(t) +z_0 \hspace{0.05cm},\hspace{0.2cm}
  z_0 = x_0 + {\rm j} \cdot y_0\hspace{0.05cm}.</math>
  z_0 = x_0 + {\rm j} \cdot y_0\hspace{0.05cm}.</math>
The graph shows this&nbsp; &raquo;'''Rice fading channel model'''&laquo;.&nbsp; As a special case, the Rayleigh model results when &nbsp; $x_0 = y_0= 0$.
<br clear=all>
The Rice fading model can be summarized as follows, see also&nbsp; [Hin08]<ref name = 'Hin08'>Hindelang, T.:&nbsp; Mobile Communications. &nbsp; Lecture notes. Institute for Communications Engineering. &nbsp; Technical University of Munich, 2008.</ref>:
*The real part&nbsp; $x(t)$&nbsp; is Gaussian distributed with mean value&nbsp; $x_0$&nbsp; and variance&nbsp; $\sigma ^2$.
*The imaginary part&nbsp; $y(t)$&nbsp; is also Gaussian distributed&nbsp; $($mean&nbsp; $y_0$,&nbsp; equal variance&nbsp; $\sigma ^2)$&nbsp; and independent of&nbsp; $x(t)$.<br>


Die Grafik zeigt dieses&nbsp; '''Rice&ndash;Fading&ndash;Kanalmodell'''.&nbsp; Als Sonderfall ergibt sich das Rayleigh&ndash;Modell, wenn man&nbsp; $x_0 =  y_0= 0$&nbsp; setzt.<br>
*For&nbsp; $z_0 \ne 0$&nbsp; the value&nbsp; $|z(t)|$&nbsp; has a [[Theory_of_Stochastic_Signals/Further_Distributions#Rice_PDF|$\text{Rice PDF}$]], from which the term&nbsp; "Rice fading"&nbsp; is derived.  
 
*To simplify the notation we set&nbsp; $|z(t)| = a(t)$. &nbsp; For&nbsp; $a < 0$&nbsp; it's PDF is&nbsp; $f_a(a) \equiv 0$,&nbsp; for&nbsp; $a \ge 0$ the following equation applies, where&nbsp; $\rm I_0(\cdot)$&nbsp; denotes the&nbsp; "modified Bessel&ndash;function" of zero order:
 
Das Rice&ndash;Fading&ndash;Modell lässt sich wie folgt zusammenfassen, siehe auch&nbsp; [Hin08]<ref name = 'Hin08'>Hindelang, T.: ''Mobile Communications''. Vorlesungsmanuskript. Lehrstuhl für Nachrichtentechnik, TU München, 2008.</ref>:
*Der Realteil&nbsp; $x(t)$&nbsp; ist gaußverteilt mit Mittelwert&nbsp; $x_0$&nbsp; und Varianz&nbsp; $\sigma ^2$.
*Der Imaginärteil&nbsp; $y(t)$&nbsp; ist ebenfalls gaußverteilt&nbsp; $($Mittelwert&nbsp; $y_0$,&nbsp; gleiche Varianz&nbsp; $\sigma ^2)$&nbsp;  sowie unabhängig von&nbsp; $x(t)$.<br>
 
*Für&nbsp; $z_0 \ne 0$&nbsp; ist der Betrag&nbsp; $|z(t)|$&nbsp; [[Stochastische_Signaltheorie/Weitere_Verteilungen#Riceverteilung| riceverteilt]], woraus die Bezeichnung &bdquo;<i>Rice&ndash;Fading</i>&rdquo; herrührt.  
*Zur Vereinfachung der Schreibweise setzen wir&nbsp; $|z(t)| = a(t)$.&nbsp; Für&nbsp; $a < 0$&nbsp; ist die Betrags&ndash;WDF&nbsp; $f_a(a) \equiv 0$,&nbsp; für&nbsp; $a \ge 0$ gilt folgende Gleichung, wobei&nbsp; $\rm I_0(\cdot)$&nbsp; die <i>modifizierte Bessel&ndash;Funktion</i> nullter Ordnung bezeichnet:


::<math>f_a(a) = \frac{a}{\sigma^2} \cdot {\rm exp} \big [ -\frac{a^2 + |z_0|^2}{2\sigma^2}\big ] \cdot {\rm I}_0 \left [ \frac{a \cdot |z_0|}{\sigma^2} \right ]\hspace{0.5cm}\text{mit}\hspace{0.5cm}{\rm I }_0 (u) = {\rm J }_0 ({\rm j} \cdot u) =  
::<math>f_a(a) = \frac{a}{\sigma^2} \cdot {\rm exp} \big [ -\frac{a^2 + |z_0|^2}{2\sigma^2}\big ] \cdot {\rm I}_0 \left [ \frac{a \cdot |z_0|}{\sigma^2} \right ]\hspace{0.5cm}\text{with}\hspace{0.5cm}{\rm I }_0 (u) = {\rm J }_0 ({\rm j} \cdot u) =  
  \sum_{k = 0}^{\infty} \frac{ (u/2)^{2k}}{k! \cdot \Gamma (k+1)}
  \sum_{k = 0}^{\infty} \frac{ (u/2)^{2k}}{k! \cdot \Gamma (k+1)}
  \hspace{0.05cm}.</math>
  \hspace{0.05cm}.</math>


*Der Mobilfunkkanal ist um so besser für die Digitalsignalübertragung geeignet, je größer die &bdquo;Direktpfadleistung&rdquo;&nbsp;   $(|z_0|^2)$&nbsp; gegenüber den Leistungen der Streukomponenten&nbsp; $(2\sigma^2)$&nbsp; ist.<br>
*The greater the direct path power&nbsp; $(|z_0|^2)$&nbsp; compared to the power of the stray components&nbsp; $(2\sigma^2)$&nbsp; the better suited for digital signal transmission is the mobile communication channel.


*Ist&nbsp; $|z_0| \gg \sigma$&nbsp; $($Faktor &nbsp;$3$&nbsp; oder mehr$)$, so  kann die Rice&ndash;WDF mit guter Näherung durch eine Gaußverteilung mit Mittelwert&nbsp; $|z_0|$&nbsp; und Streuung&nbsp; $\sigma$&nbsp; angenähert werden.<br>
*If &nbsp; $|z_0| \gg \sigma$&nbsp; $($factor &nbsp;$3$&nbsp; or more$)$, the Rice PDF can be approximated accurately by a Gaussian distribution with mean&nbsp; $|z_0|$&nbsp; and variance&nbsp; $\sigma^2$. <br>


*Im Gegensatz zum&nbsp; <i>Rayleigh&ndash;Fading</i> &nbsp; &rArr; &nbsp; $z_0 \equiv 0$ ist die Phase bei&nbsp; <i>Rice&ndash;Fading</i>&nbsp; nicht gleichverteilt, sondern es gibt eine Vorzugsrichtung&nbsp; $\phi_0 = \arctan(y_0/x_0)$. Oft setzt man&nbsp; $y_0 = 0$ &nbsp; &#8658; &nbsp; $\phi_0 = 0$.<br>
*In contrast to&nbsp; Rayleigh fading &nbsp; &rArr; &nbsp; $z_0 \equiv 0$, the phase at&nbsp; Rice fading&nbsp; is not equally distributed, but there is a preferred direction&nbsp; $\phi_0 = \arctan(y_0/x_0)$.&nbsp; Often one sets&nbsp; $y_0 = 0$ &nbsp; &#8658; &nbsp; $\phi_0 = 0$.<br>


== Beispielhafte Signalverläufe bei Rice–Fading==
== Example of signal behaviour with Rice fading==
<br>
<br>
[[File:P ID2129 Mob T 1 4 S2 v1.png|right|frame|Vergleich von Rayleigh-Fading (blau) und Rice-Fading (rot)|class=fit]]
[[File:P ID2129 Mob T 1 4 S2 v1.png|right|frame|Comparison of Rayleigh fading (blue) and Rice fading (red)|class=fit]]
Die Grafik zeigt typische Signalverläufe und Dichtefunktionen zweier Mobilfunkkanäle:
The diagram shows typical signal characteristics and density functions of two mobile communication channels:
*Rayleigh&ndash;Fading&nbsp; (blaue Kurven)&nbsp; mit&nbsp;  
*Rayleigh fading&nbsp; (blue curves)&nbsp; with&nbsp;  
:$${\rm E}\big [|z(t))|^2\big ] = 2 \cdot \sigma^2 = 1,$$
:$${\rm E}\big [|z(t))|^2\big ] = 2 \cdot \sigma^2 = 1,$$


*Rice&ndash;Fading&nbsp; (rote Kurven)&nbsp; mit gleichem&nbsp; $\sigma$&nbsp; sowie&nbsp;
*Rice fading&nbsp; (red curves)&nbsp; with same&nbsp; $\sigma$&nbsp; and
:$$x_0 = 0.707,\ \ y_0 = -0.707.$$
:$$x_0 = 0.707,\ \ y_0 = -0.707.$$


Für die Erzeugung der Signalausschnitte nach obigem Modell wurde jeweils die&nbsp; [[Mobile_Kommunikation/Statistische_Bindungen_innerhalb_des_Rayleigh%E2%80%93Prozesses#Dopplerfrequenz_und_deren_Verteilung| maximale Dopplerfrequenz]]&nbsp; $f_\text{D, max} = 100 \ \rm Hz$&nbsp; zugrundegelegt.  
For the generation of the signals according to the above model, the&nbsp; [[Mobile_Communications/Statistical_Bindings_within_the_Rayleigh_Process#Doppler_frequency_and_its_distribution|$\text{maximum Doppler frequency}$]]&nbsp; $f_\text{D, max} = 100 \ \rm Hz$&nbsp; was used as reference.  


Autokorrelationsfunktion&nbsp; $\rm (AKF)$&nbsp; und Leistungsdichtespektrum&nbsp; $\rm (LDS)$&nbsp; von Rayleigh und Rice unterscheiden sich bei ansonstern angepassten Parameterwerten nur geringfügig.&nbsp; Es gilt:
The auto-correlation function&nbsp; $\rm (ACF)$&nbsp; and power-spectral density&nbsp; $\rm (PSD)$&nbsp; of Rayleigh and Rice differ only slightly, other than adjusted parameter values.&nbsp; The following applies:


::<math>\varphi_z ({\rm \Delta}t)\Bigg |_{\hspace{0.1cm}{\rm Rice}}  \hspace{-0.5cm}  =  \varphi_z ({\rm \Delta}t)\Bigg |_{\hspace{0.1cm}{\rm Rayleigh}} \hspace{-0.8cm} + |z_0|^2 \hspace{0.05cm},</math>
::<math>\varphi_z ({\rm \Delta}t)\Bigg |_{\hspace{0.1cm}{\rm Rice}}  \hspace{-0.5cm}  =  \varphi_z ({\rm \Delta}t)\Bigg |_{\hspace{0.1cm}{\rm Rayleigh}} \hspace{-0.8cm} + |z_0|^2 \hspace{0.05cm},</math>
::<math> {\it \Phi}_z(f_{\rm D})\Bigg |_{\hspace{0.1cm}{\rm Rice}} \hspace{-0.5cm}  =    {\it \Phi}_z(f_{\rm D})\Bigg |_{\hspace{0.1cm}{\rm Rayleigh}} \hspace{-0.8cm} + |z_0|^2 \cdot \delta (f_{\rm D}) \hspace{0.05cm}.</math>
::<math> {\it \Phi}_z(f_{\rm D})\Bigg |_{\hspace{0.1cm}{\rm Rice}} \hspace{-0.5cm}  =    {\it \Phi}_z(f_{\rm D})\Bigg |_{\hspace{0.1cm}{\rm Rayleigh}} \hspace{-0.8cm} + |z_0|^2 \cdot \delta (f_{\rm D}) \hspace{0.05cm}.</math>


Berücksichtigt ist, dass die Spektraldarstellung eines  Gleichanteils zu einer Diracfunktion führt.<br>
It is taken into account that the spectral representation of a DC component leads to a Dirac delta function.<br>
<br clear= all>
<br clear= all>
Zu dieser Grafik ist anzumerken:
It should be noted about this graph:
*Die Realteile&nbsp; $x(t)$&nbsp; von Rayleigh (blau) und Rice (rot) unterscheiden sich durch die Konstante&nbsp; $x_0 = 0.707$.&nbsp; Die statistischen Eigenschaften sind ansonsten gleich: &nbsp; Gaußsche WDF&nbsp; $f_x(x)$&nbsp; mit Streuung&nbsp; $\sigma = 0.707$, entweder mittelwertfrei (Rayleigh) oder mit Mittelwert&nbsp; $x_0$&nbsp; (Rice).<br>
*The real parts&nbsp; $x(t)$&nbsp; of Rayleigh (blue) and Rice (red) only differ by the constant&nbsp; $x_0 = 0.707$. &nbsp; The statistical properties are otherwise the same: &nbsp; Gaussian PDF $f_x(x)$&nbsp; with standard deviation&nbsp; $\sigma = 0.707$, either zero-mean (Rayleigh) or with mean&nbsp; $x_0$&nbsp; (Rice).<br>


*Im Imaginärteil&nbsp; $y(t)$&nbsp; erkennt man bei Rice zusätzlich die Gleichkomponente&nbsp; $y_0 = -0.707$.&nbsp; Die (hier nicht dargestellte) WDF&nbsp; $f_y(y)$&nbsp; ist somit eine Gaußkurve mit der Streuung&nbsp; $\sigma = 0.707$&nbsp; um den Mittelwert&nbsp; $ y_0 = -0.707$, also achsensymmetrisch zur skizzierten WDF&nbsp; $f_x(x)$.<br>
*In the imaginary part&nbsp; $y(t)$&nbsp; of the Rice distribution one can additionally recognize the direct component&nbsp; $y_0 = -0.707$.&nbsp; The (here not shown) PDF $f_y(y)$&nbsp; is thus a Gaussian curve with the standard deviation&nbsp; $\sigma = 0. 707$&nbsp; around the mean value&nbsp; $ y_0 = -0.707$, thus axisymmetrical to the shown PDF $f_x(x)$.<br>


*Die (logarithmische) Betragsdarstellung &nbsp; &#8658; &nbsp; $a(t) =|z(t)|$   zeigt, dass die rote Kurve meist oberhalb der blauen liegt.&nbsp; Dies ist auch aus der WDF&nbsp; $f_a(a)$&nbsp; ablesbar.  
*The (logarithmic) representation of &nbsp; &#8658; &nbsp; $a(t) =|z(t)|$ shows that the red curve is usually above the blue one.&nbsp; This can also be read from the PDF $f_a(a)$&nbsp;.  
*Beim Rice&ndash;Kanal ist die Fehlerwahrscheinlichkeit unter Berücksichtigung von AWGN&ndash;Rauschen niedriger als bei Rayleigh, da der Empfänger über den Rice&ndash;Direktpfad viel nutzbare Energie erhält.<br>
*For the Rice channel, the error probability is lower than for Rayleigh when AWGN is taken into account, since the receiver gets some usable energy via the Rice direct path.


*Die WDF&nbsp; $f_\phi(\phi)$&nbsp; zeigt den Vorzugswinkel&nbsp; $\phi \approx 45^\circ$&nbsp; des vorliegenden  Rice&ndash;Kanals.&nbsp; Der komplexe Faktor&nbsp; $z(t)$&nbsp; befindet sich  wegen&nbsp; $x_0 > 0$&nbsp; und&nbsp; $y_0 < 0$&nbsp; großteils im vierten Quadranten, während beim Rayleigh&ndash;Kanal alle Quadranten gleichwahrscheinlich sind.<br>
*The PDF $f_\phi(\phi)$&nbsp; shows the preferred angle&nbsp; $\phi \approx -45^\circ$&nbsp; of the given Rice channel &nbsp; The complex factor&nbsp; $z(t)$&nbsp; is located mainly in the fourth quadrant because of&nbsp; $x_0 > 0$&nbsp; and&nbsp; $y_0 < 0$&nbsp;, whereas in the Rayleigh channel all quadrants are equally probable.<br>


==Aufgaben zum Kapitel==
==Exercises for the chapter==
<br>
<br>
[[Aufgaben:Aufgabe_1.6:_AKF_und_LDS_bei_Rice–Fading|Aufgabe 1.6: AKF und LDS bei Rice–Fading]]
[[Aufgaben:Exercise 1.6: Autocorrelation Function and PSD with Rice Fading]]


[[Aufgabe_1.6Z:_Rayleigh_und_Rice_im_Vergleich|Aufgabe 1.6Z: Rayleigh und Rice im Vergleich]]
[[Aufgaben:Exercise 1.6Z: Comparison of Rayleigh and Rice]]


[[Aufgaben:1.7 WDF des Rice–Fadings|Aufgabe 1.7: WDF des Rice–Fadings]]
[[Aufgaben:Exercise 1.7: PDF of Rice Fading]]


==Quellenverzeichnis==
==References==


{{Display}}
{{Display}}
[[de:Mobile_Kommunikation/Nichtfrequenzselektives_Fading_mit_Direktkomponente]]

Latest revision as of 14:28, 16 March 2026

Channel model and Rice PDF


The  $\text{Rayleigh distribution}$  describes the mobile communication channel under the assumption that there is no direct path and thus the multiplicative factor  $z(t) = x(t) + {\rm j} \cdot y(t)$  is solely composed of diffusely scattered components.

If a direct component  $($Line of Sight,  $\rm LoS)$  is present, it is necessary to add direct components   $x_0$  and/or  $y_0$  to the zero mean Gaussian processes   $x(t)$  and  $y(t)$:

Rice fading channel model
[math]\displaystyle{ x(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} x(t) +x_0 \hspace{0.05cm}, \hspace{0.2cm} y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} y(t) +y_0\hspace{0.05cm}, }[/math]
[math]\displaystyle{ z(t) = x(t) + {\rm j} \cdot y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} z(t) +z_0 \hspace{0.05cm},\hspace{0.2cm} z_0 = x_0 + {\rm j} \cdot y_0\hspace{0.05cm}. }[/math]

The graph shows this  »Rice fading channel model«.  As a special case, the Rayleigh model results when   $x_0 = y_0= 0$.
The Rice fading model can be summarized as follows, see also  [Hin08][1]:

  • The real part  $x(t)$  is Gaussian distributed with mean value  $x_0$  and variance  $\sigma ^2$.
  • The imaginary part  $y(t)$  is also Gaussian distributed  $($mean  $y_0$,  equal variance  $\sigma ^2)$  and independent of  $x(t)$.
  • For  $z_0 \ne 0$  the value  $|z(t)|$  has a $\text{Rice PDF}$, from which the term  "Rice fading"  is derived.
  • To simplify the notation we set  $|z(t)| = a(t)$.   For  $a < 0$  it's PDF is  $f_a(a) \equiv 0$,  for  $a \ge 0$ the following equation applies, where  $\rm I_0(\cdot)$  denotes the  "modified Bessel–function" of zero order:
[math]\displaystyle{ f_a(a) = \frac{a}{\sigma^2} \cdot {\rm exp} \big [ -\frac{a^2 + |z_0|^2}{2\sigma^2}\big ] \cdot {\rm I}_0 \left [ \frac{a \cdot |z_0|}{\sigma^2} \right ]\hspace{0.5cm}\text{with}\hspace{0.5cm}{\rm I }_0 (u) = {\rm J }_0 ({\rm j} \cdot u) = \sum_{k = 0}^{\infty} \frac{ (u/2)^{2k}}{k! \cdot \Gamma (k+1)} \hspace{0.05cm}. }[/math]
  • The greater the direct path power  $(|z_0|^2)$  compared to the power of the stray components  $(2\sigma^2)$  the better suited for digital signal transmission is the mobile communication channel.
  • If   $|z_0| \gg \sigma$  $($factor  $3$  or more$)$, the Rice PDF can be approximated accurately by a Gaussian distribution with mean  $|z_0|$  and variance  $\sigma^2$.
  • In contrast to  Rayleigh fading   ⇒   $z_0 \equiv 0$, the phase at  Rice fading  is not equally distributed, but there is a preferred direction  $\phi_0 = \arctan(y_0/x_0)$.  Often one sets  $y_0 = 0$   ⇒   $\phi_0 = 0$.

Example of signal behaviour with Rice fading


Comparison of Rayleigh fading (blue) and Rice fading (red)

The diagram shows typical signal characteristics and density functions of two mobile communication channels:

  • Rayleigh fading  (blue curves)  with 
$${\rm E}\big [|z(t))|^2\big ] = 2 \cdot \sigma^2 = 1,$$
  • Rice fading  (red curves)  with same  $\sigma$  and
$$x_0 = 0.707,\ \ y_0 = -0.707.$$

For the generation of the signals according to the above model, the  $\text{maximum Doppler frequency}$  $f_\text{D, max} = 100 \ \rm Hz$  was used as reference.

The auto-correlation function  $\rm (ACF)$  and power-spectral density  $\rm (PSD)$  of Rayleigh and Rice differ only slightly, other than adjusted parameter values.  The following applies:

[math]\displaystyle{ \varphi_z ({\rm \Delta}t)\Bigg |_{\hspace{0.1cm}{\rm Rice}} \hspace{-0.5cm} = \varphi_z ({\rm \Delta}t)\Bigg |_{\hspace{0.1cm}{\rm Rayleigh}} \hspace{-0.8cm} + |z_0|^2 \hspace{0.05cm}, }[/math]
[math]\displaystyle{ {\it \Phi}_z(f_{\rm D})\Bigg |_{\hspace{0.1cm}{\rm Rice}} \hspace{-0.5cm} = {\it \Phi}_z(f_{\rm D})\Bigg |_{\hspace{0.1cm}{\rm Rayleigh}} \hspace{-0.8cm} + |z_0|^2 \cdot \delta (f_{\rm D}) \hspace{0.05cm}. }[/math]

It is taken into account that the spectral representation of a DC component leads to a Dirac delta function.

It should be noted about this graph:

  • The real parts  $x(t)$  of Rayleigh (blue) and Rice (red) only differ by the constant  $x_0 = 0.707$.   The statistical properties are otherwise the same:   Gaussian PDF $f_x(x)$  with standard deviation  $\sigma = 0.707$, either zero-mean (Rayleigh) or with mean  $x_0$  (Rice).
  • In the imaginary part  $y(t)$  of the Rice distribution one can additionally recognize the direct component  $y_0 = -0.707$.  The (here not shown) PDF $f_y(y)$  is thus a Gaussian curve with the standard deviation  $\sigma = 0. 707$  around the mean value  $ y_0 = -0.707$, thus axisymmetrical to the shown PDF $f_x(x)$.
  • The (logarithmic) representation of   ⇒   $a(t) =|z(t)|$ shows that the red curve is usually above the blue one.  This can also be read from the PDF $f_a(a)$ .
  • For the Rice channel, the error probability is lower than for Rayleigh when AWGN is taken into account, since the receiver gets some usable energy via the Rice direct path.
  • The PDF $f_\phi(\phi)$  shows the preferred angle  $\phi \approx -45^\circ$  of the given Rice channel   The complex factor  $z(t)$  is located mainly in the fourth quadrant because of  $x_0 > 0$  and  $y_0 < 0$ , whereas in the Rayleigh channel all quadrants are equally probable.

Exercises for the chapter


Aufgaben:Exercise 1.6: Autocorrelation Function and PSD with Rice Fading

Aufgaben:Exercise 1.6Z: Comparison of Rayleigh and Rice

Aufgaben:Exercise 1.7: PDF of Rice Fading

References

  1. Hindelang, T.:  Mobile Communications.   Lecture notes. Institute for Communications Engineering.   Technical University of Munich, 2008.