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

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== 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.  
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The&nbsp; [[Mobile_Communication/Probability_density_of_Rayleigh_fading#A very general description of the mobile communication channel| 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]]
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[[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:
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If a direct component&nbsp; $($englisch:&nbsp; <i>Line of Sight</i>,&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; $y(t)$&nbsp; :
  
 
::<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>
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::<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>
 
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The graphic shows this&nbsp; '''Rice&ndash;Fading&ndash;Channel model'''.&nbsp; As a special case, the Rayleigh&ndash;model results when &nbsp; $x_0 = y_0= 0$&nbsp;.<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>
 
  
  
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>:
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The Rice&ndash;Fading&ndash;model can be summarized as follows, see also&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; $\sigma ^2$.  
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*The real part&nbsp; $x(t)$&nbsp; is gaussian distributed with mean value&nbsp; $x_0$&nbsp; and variance&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>
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*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>
  
*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.  
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*For&nbsp; $z_0 \ne 0$&nbsp; the value &nbsp; $|z(t)|$&nbsp; is [[Stochastic_Signal Theory/further_distributions#Riceversion| riceversified]], from which the term &bdquo;<i>Rice&ndash;Fading</i>&rdquo; is derived.  
*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:
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*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 <i>modified Bessel&ndash;function</i> of zero order:
  
 
::<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{mit}\hspace{0.5cm}{\rm I }_0 (u) = {\rm J }_0 ({\rm j} \cdot u) =  
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  \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>
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*The greater the &bdquo;direct path power&rdquo;&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 communications 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>
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*If &nbsp; $|z_0| \gg \sigma$&nbsp; $($factor &nbsp;$3$&nbsp; or more$)$, the Rice&ndash;PDF can be approximated accurately by a Gaussian distribution with mean&nbsp; $|z_0|$&nbsp; and variance&nbsp; $\sigma$&nbsp; <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>
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*In contrast to&nbsp; <i>Rayleigh fading</i> &nbsp; &rArr; &nbsp; $z_0 \equiv 0$, the phase at&nbsp; <i>Rice fading</i>&nbsp; is not equally distributed, but there is a preferred direction&nbsp; $\phi_0 = \arctan(y_0/x_0)$. Often one sets&nbsp; $y_0 = 0$ &nbsp; &#8658; &nbsp; $\phi_0 = 0$.<br>
  
== Beispielhafte Signalverläufe bei Rice–Fading==
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== 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]]
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[[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:
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The diagram shows typical signal characteristics and density functions of two mobile communication channels:
*Rayleigh&ndash;Fading&nbsp; (blaue Kurven)&nbsp; mit&nbsp;  
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*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;
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*Rice fading&nbsp; (red curves)&nbsp; with the same&nbsp; $\sigma$&nbsp; and&nbsp  
 
:$$x_0 = 0.707,\ \ y_0 = -0.707.$$
 
:$$x_0 = 0.707,\ \ y_0 = -0.707.$$
  
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.  
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For the generation of the signal sections according to the above model, the&nbsp; [[Mobile_Communication/Statistical_Bonds_within_the_Rayleigh_process#Doppler_frequency_and_its_distribution|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:
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The autocorrelation 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>
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It is taken into account that the spectral representation of a DC component leads to a Dirac function.<br>
 
<br clear= all>
 
<br clear= all>
Zu dieser Grafik ist anzumerken:
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It should be noted about this graphic:
*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>
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*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&nbsp; $f_x(x)$&nbsp; with variance&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>
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*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&nbsp; $f_y(y)$&nbsp; is thus a Gaussian curve with the variance&nbsp; $\sigma = 0. 707$&nbsp; around the mean value&nbsp; $ y_0 = -0.707$, thus axisymmetrical to the shown PDF&nbsp; $f_x(x)$.<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.  
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*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&nbsp; $f_a(a)$&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>
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*For the Rice channel, the error probability is lower than for Rayleigh when AWGN is taken into account, since the receiver gets a lot of 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>
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*The PDF&nbsp; $f_\phi(\phi)$&nbsp; shows the preferred angle&nbsp; $\phi \approx 45^\circ$&nbsp; of the given Rice&ndash;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==
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==Exercises zum Kapitel==
 
<br>
 
<br>
[[Aufgaben:Aufgabe_1.6:_AKF_und_LDS_bei_Rice–Fading|Aufgabe 1.6: AKF und LDS bei Rice–Fading]]
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[[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]]
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[[Aufgaben:Exercise 1.6Z: Comparison of Rayleigh and Rice]]
  
[[Aufgaben:1.7 WDF des Rice–Fadings|Aufgabe 1.7: WDF des Rice–Fadings]]
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[[Aufgaben:Exercise 1.7: PDF of Rice Fading]]
  
==Quellenverzeichnis==
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==List of sources==
  
 
{{Display}}
 
{{Display}}

Revision as of 20:34, 6 July 2020

Channel model and Rice PDF


The  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.

Rice-Fading channel model

If a direct component  $($englisch:  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  $y(t)$  :

\[x(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} x(t) +x_0 \hspace{0.05cm}, \hspace{0.2cm} y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} y(t) +y_0\hspace{0.05cm},\]
\[z(t) = x(t) + {\rm j} \cdot y(t) \hspace{0.1cm} \Rightarrow \hspace{0.1cm} z(t) +z_0 \hspace{0.05cm},\hspace{0.2cm} z_0 = x_0 + {\rm j} \cdot y_0\hspace{0.05cm}.\]

The graphic 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   $|z(t)|$  is riceversified, 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:
\[f_a(a) = \frac{a}{\sigma^2} \cdot {\rm exp} \big [ -\frac{a^2 + |z_0|^2}{2\sigma^2}\big ] \cdot {\rm I}_0 \left [ \frac{a \cdot |z_0|}{\sigma^2} \right ]\hspace{0.5cm}\text{mit}\hspace{0.5cm}{\rm I }_0 (u) = {\rm J }_0 ({\rm j} \cdot u) = \sum_{k = 0}^{\infty} \frac{ (u/2)^{2k}}{k! \cdot \Gamma (k+1)} \hspace{0.05cm}.\]
  • 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 communications 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  $\sigma$ 
  • 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 the same  $\sigma$  and&nbsp
$$x_0 = 0.707,\ \ y_0 = -0.707.$$

For the generation of the signal sections according to the above model, the  maximum_Doppler_frequency  $f_\text{D, max} = 100 \ \rm Hz$  was used as reference.

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

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

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

It should be noted about this graphic:

  • 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 variance  $\sigma = 0.707$, 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 variance  $\sigma = 0. 707$  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 a lot of 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 zum Kapitel


Exercise 1.6: Autocorrelation Function and PSD with Rice Fading

Exercise 1.6Z: Comparison of Rayleigh and Rice

Exercise 1.7: PDF of Rice Fading

List of sources

  1. Hindelang, T.: Mobile Communications. Vorlesungsmanuskript. Lehrstuhl für Nachrichtentechnik, TU München, 2008.