Difference between revisions of "Digital Signal Transmission/Properties of Nyquist Systems"

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{{Header
 
{{Header
|Untermenü=Digitalsignalübertragung bei idealisierten Bedingungen
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|Untermenü=Digital Signal Transmission under Idealized Conditions
 
|Vorherige Seite=Fehlerwahrscheinlichkeit bei Basisbandübertragung
 
|Vorherige Seite=Fehlerwahrscheinlichkeit bei Basisbandübertragung
 
|Nächste Seite=Optimierung der Basisbandübertragungssysteme
 
|Nächste Seite=Optimierung der Basisbandübertragungssysteme
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== Erstes Nyquistkriterium im Zeitbereich ==
+
== First Nyquist criterion in the time domain ==
 
<br>
 
<br>
Für das gesamte erste  Hauptkapitel wurde vorausgesetzt, dass die Detektion eines Symbols nicht durch Nachbarimpulse beeinträchtigt werden soll. Dies erreicht man durch die Detektion des Signals
+
For the entire first main chapter it was assumed that the detection of a symbol should not be affected by neighboring pulses.&nbsp; This is achieved by the detection of the signal
:$$d(t) =  \sum \limits_{\it (\nu)} a_\nu \cdot g_d ( t - \nu T)$$
+
:$$d(t) =  d_{\rm S}(t) = \sum \limits_{\it (\nu)} a_\nu \cdot g_d ( t - \nu T)$$
zu den Detektionszeitpunkten &nbsp;$(\nu \cdot T)$&nbsp; immer dann, wenn der Detektionsgrundimpuls &nbsp;$g_d(t)$
+
at the detection times &nbsp;$(\nu \cdot T)$&nbsp; whenever the basic detection pulse &nbsp;$g_d(t)$
*auf den Bereich &nbsp;$|t| < T$&nbsp; beschränkt ist, was für das letzte Kapitel &nbsp;[[Digitalsignalübertragung/Fehlerwahrscheinlichkeit_bei_Basisbandübertragung|Fehlerwahrscheinlichkeit bei Basisbandübertragung]]&nbsp; vorausgesetzt wurde, oder
+
*is restricted to the range &nbsp;$|t| < T$,&nbsp; which was assumed for the last chapter &nbsp;[[Digital_Signal_Transmission/Fehlerwahrscheinlichkeit_bei_Basisbandübertragung|"Error Probability for Baseband Transmission"]], &nbsp; or
*äquidistante Nulldurchgänge zu den Detektionszeitpunkten &nbsp;$\nu \cdot T$&nbsp; aufweist.
+
*has equidistant zero crossings at the detection times &nbsp;$\nu \cdot T$.&nbsp;  
  
  
Aus Gründen einer möglichst einfachen Darstellung wird im Folgenden das Detektionsstörsignal als vernachlässigbar klein angenommen &nbsp;$(d_{\rm N}(t) =0)$.
+
For the sake of simplicity,&nbsp; the noise component of the detection signal is assumed to be negligibly small in the following &nbsp; &rArr; &nbsp; $d_{\rm N}(t) =0$.
  
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
$\text{Definition:}$&nbsp; Man bezeichnet einen Detektionsgrundimpuls mit den Eigenschaften
+
$\text{Definition:}$&nbsp; One denotes a basic detection pulse  with the properties
:$$g_d ( t = \nu  T)= 0 \hspace{0.3cm}{\rm{f\ddot{u}r} }\hspace{0.3cm}
+
:$$g_d ( t = \nu  T)= 0 \hspace{0.3cm}{\rm{for} }\hspace{0.3cm}
 
\nu = \pm 1, \pm 2,\pm 3,\hspace{0.05cm}\text{...}$$
 
\nu = \pm 1, \pm 2,\pm 3,\hspace{0.05cm}\text{...}$$
als '''Nyquistimpuls''' &nbsp;$g_{\hspace{0.05cm}\rm Nyq}(t)$, benannt nach dem Physiker &nbsp;[https://de.wikipedia.org/wiki/Harry_Nyquist Harry Nyquist].}}  
+
as&nbsp; '''Nyquist pulse''' &nbsp;$g_{\hspace{0.05cm}\rm Nyq}(t)$,&nbsp; named after the physicist &nbsp;[https://en.wikipedia.org/wiki/Harry_Nyquist "Harry Nyquist"].}}  
  
  
[[File:P_ID1272__Dig_T_1_3_S1_v1.png|right|frame|Detektionssignal bei Nyquistimpulsformung]]
+
{{GraueBox|TEXT=
{{GraueBox|TEXT=  
+
[[File:P_ID1272__Dig_T_1_3_S1_v1.png|right|frame|Detection signal with Nyquist pulse shaping]]   
$\text{Beispiel 1:}$&nbsp; Die Grafik zeigt das Detektionssignal &nbsp;$d(t)$&nbsp; eines solchen Nyquistsystems. Rot gepunktet sind die (gewichteten und verschobenen) Nyquistimpulse &nbsp;$a_\nu \cdot g_{\hspace{0.05cm}\rm Nyq}(t -\nu \cdot T)$&nbsp; eingezeichnet.
+
$\text{Example 1:}$&nbsp; The diagram shows the detection signal &nbsp;$d(t)$&nbsp; of such a Nyquist system.&nbsp; Dotted in red are the&nbsp; (weighted and shifted)&nbsp; Nyquist pulses &nbsp;$a_\nu \cdot g_{\hspace{0.05cm}\rm Nyq}(t -\nu \cdot T)$.&nbsp;  
  
Bitte beachten Sie:
+
Please note:  
*Zu den Detektionszeitpunkten gilt &nbsp;$d(\nu \cdot T) = a_\nu \cdot g_{\hspace{0.05cm}\rm Nyq}(0)$, wie aus den blauen Kreisen und dem grünen Raster hervorgeht.  
+
*At the detection times hold &nbsp; $d(\nu \cdot T) = a_\nu \cdot g_{\hspace{0.05cm}\rm Nyq}(0)$,&nbsp; as shown by the blue circles and the green grid.
*Die Nachläufer der vorangegangenen Impulse &nbsp;$(\nu < 0)$&nbsp; sowie die Vorläufer der nachfolgenden Impulse &nbsp;$(\nu > 0)$&nbsp; beeinflussen beim Nyquistsystem die Detektion des Symbols &nbsp;$a_0$&nbsp; nicht.
+
*The trailing edge &nbsp; &rArr; &nbsp; "trailers"&nbsp; of preceding pulses &nbsp;$(\nu < 0)$&nbsp; as well as the rising edge &nbsp; &rArr; &nbsp; "precursors"&nbsp; of following pulses &nbsp;$(\nu > 0)$&nbsp; do not affect the detection of the symbol &nbsp;$a_0$&nbsp; in the Nyquist system.
  
  
Der Vollständigkeit halber sei erwähnt, dass für diese Grafik der Detektionsgrundimpuls
+
It should be mentioned that this graph is valid for the basic detection pulse  with trapezoidal spectrum and rolloff factor &nbsp;$r = 0.5$:
:$$g_{\hspace{0.05cm}\rm Nyq} ( t )= g_0 \cdot {\rm si} \left ( \frac{\pi \cdot
+
:$$g_{\hspace{0.05cm}\rm Nyq} ( t )= g_0 \cdot {\rm sinc} \left ( \frac{t}{T}\right)\cdot {\rm sinc} \left ( \frac{ t}{2 \cdot
t}{T}\right)\cdot {\rm si} \left ( \frac{\pi \cdot t}{2 \cdot
+
T}\right),$$
T}\right)$$
+
which has already been discussed in the section &nbsp;[[Linear_and_Time_Invariant_Systems/Some_Low-Pass_Functions_in_Systems_Theory#Trapezoidal_low-pass_filter|"Trapezoidal low-pass filter"]]&nbsp; of the book&nbsp; "Linear Time Invariant Systems".}}
mit trapezförmigem Spektrum und dem Rolloff&ndash;Faktor &nbsp;$r = 0.5$&nbsp; zugrunde liegt, der schon auf der Seite &nbsp;[[Lineare_zeitinvariante_Systeme/Einige_systemtheoretische_Tiefpassfunktionen#Trapez.E2.80.93Tiefpass|Trapeztiefpass]]&nbsp; des Buches &bdquo;Lineare zeitinvariante Systeme&rdquo; behandelt wurde.}}
 
  
  
== Erstes Nyquistkriterium im Frequenzbereich ==
+
== First Nyquist criterion in the frequency domain ==
 
<br>
 
<br>
[https://de.wikipedia.org/wiki/Harry_Nyquist Harry Nyquist]&nbsp; hat die Bedingung für eine impulsinterferenzfreie Detektion nicht nur für den Zeitbereich formuliert, sondern 1928 auch das entsprechende Kriterium im Frequenzbereich angegeben.
+
[https://en.wikipedia.org/wiki/Harry_Nyquist "Harry Nyquist"]&nbsp; formulated the condition for detection without intersymbol interfering not only for the time domain,&nbsp; but in 1928 he also gave the corresponding criterion in the frequency domain.
  
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
$\text{Erstes Nyquistkriterium:}$&nbsp; Erfüllt das Spektrum &nbsp;$G_d(f)$&nbsp;  des Detektionsgrundimpulses &nbsp;$g_d(t)$&nbsp; die Bedingung
+
$\text{First Nyquist criterion:}$&nbsp; If the spectrum &nbsp;$G_d(f)$&nbsp;  of the basic detection pulse  &nbsp;$g_d(t)$&nbsp; fulfills the condition
:$$\sum \limits_{\it k = -\infty}^{+\infty} G_d \left ( f - \frac{k}{T} \right)=
+
:$$\sum \limits_{\it k = -\infty}^{+\infty} G_d \left ( f - {k}/{T} \right)=
 
g_0 \cdot T = {\rm const.} \hspace{0.05cm}, $$
 
g_0 \cdot T = {\rm const.} \hspace{0.05cm}, $$
so ist &nbsp;$g_d(t)$&nbsp; ein Nyquistimpuls
+
then &nbsp;$g_d(t)$&nbsp; is a Nyquist pulse
*mit äquidistanten Nulldurchgängen zu den Zeitpunkten  &nbsp;$\nu \cdot T$&nbsp; für &nbsp;$\nu \ne 0$&nbsp; und
+
*with equidistant zero crossings at the times &nbsp;$\nu \cdot T$&nbsp; for &nbsp;$\nu \ne 0$&nbsp; and
*der Amplitude &nbsp;$g_d(t = 0) = g_0$.   
+
*the amplitude &nbsp;$g_d(t = 0) = g_0$.   
  
  
<i>Hinweis</i>: &nbsp; Der Beweis folgt auf der &nbsp;[[Digitalsignal%C3%BCbertragung/Eigenschaften_von_Nyquistsystemen#Beweis_des_ersten_Nyquistkriteriums|nächsten Seite]].}}
+
$\text{Note}$:&nbsp; The proof follows in the &nbsp;[[Digital_Signal_Transmission/Properties_of_Nyquist_Systems#Proof_of_the_first_Nyquist_criterion|"next section"]].}}
  
  
[[File:P_ID1273__Dig_T_1_3_S2_v1.png|right|frame|Zur Verdeutlichung des ersten Nyquistkriteriums|class=fit]]
 
 
{{GraueBox|TEXT=   
 
{{GraueBox|TEXT=   
$\text{Beispiel 2:}$&nbsp; Skizziert sind zwei Nyquistspektren &nbsp;$G_1(f)$&nbsp; und &nbsp;$G_2(f)$, die sich aus rechteckförmigen und dreieckförmigen Teilstücken zusammensetzen:  
+
$\text{Example 2:}$&nbsp; Sketched are two Nyquist spectra &nbsp;$G_1(f)$&nbsp; and &nbsp;$G_2(f)$, which are composed of rectangular and triangular segments:
  
*Das links skizzierte rein reelle Spektrum
+
The purely real spectrum sketched&nbsp; $G_1(f)$&nbsp; on the left satisfies the condition formulated above with the smallest possible bandwidth:
 +
[[File:P_ID1273__Dig_T_1_3_S2_v1.png|right|frame|Illustration of the first Nyquist criterion|class=fit]]
 
:$$G_1(f)  \hspace{-0.05cm}=\hspace{-0.05cm}  \left\{ \begin{array}{c} g_0 \cdot T  \\
 
:$$G_1(f)  \hspace{-0.05cm}=\hspace{-0.05cm}  \left\{ \begin{array}{c} g_0 \cdot T  \\
 
  0 \\  \end{array} \right.
 
  0 \\  \end{array} \right.
\begin{array}{*{1}c} \text{für}
+
\begin{array}{*{1}c} \text{for}
\\ \text{für}  \\ \end{array}\begin{array}{*{20}c}
+
\\ \text{for}  \\ \end{array}\begin{array}{*{20}c}
 
\vert f \vert \hspace{-0.08cm}<\hspace{-0.08cm} {1}/(2T), \\
 
\vert f \vert \hspace{-0.08cm}<\hspace{-0.08cm} {1}/(2T), \\
\vert f \vert \hspace{-0.08cm}>\hspace{-0.08cm} {1}/(2T)  \\
+
\vert f \vert \hspace{-0.08cm}>\hspace{-0.08cm} {1}/(2T),   \\
 
\end{array}$$
 
\end{array}$$
:erfüllt die oben formulierte Bedingung und zwar mit der kleinstmöglichen Bandbreite. Allerdings klingt der dazugehörige Nyquistimpuls &nbsp;$g_1(t) = g_0 \cdot {\rm si}(\pi \cdot t/T)$&nbsp;  sehr langsam ab, nämlich asymptotisch mit &nbsp;$1/t$.
+
But the associated Nyquist pulse &nbsp;$g_1(t) = g_0 \cdot {\rm sinc}(t/T)$&nbsp;  decays very slowly, asymptotically with &nbsp;$1/t$.
  
*Der rechts oben dargestellte Realteil des Spektrums &nbsp;$G_2(f)$&nbsp; wurde aus dem Rechteckspektrum  &nbsp;$G_1(f)$&nbsp; durch Verschiebung von Teilstücken um &nbsp;$1/T$&nbsp; nach rechts oder links konstruiert.
 
  
 
+
The real part of the spectrum &nbsp;$G_2(f)$&nbsp; shown on the upper right was constructed from the rectangular spectrum by&nbsp;$G_1(f)$&nbsp; by shifting parts of them  by &nbsp;$1/T$&nbsp; to the right or to the left.&nbsp;
$G_2(f)$&nbsp; ist ebenfalls ein Nyquistspektrum wegen
+
*$G_2(f)$&nbsp; is also a Nyquist spectrum because of
 
:$$\sum \limits_{\it k = -\infty}^{+\infty} {\rm Re}\big[G_2 \left ( f -
 
:$$\sum \limits_{\it k = -\infty}^{+\infty} {\rm Re}\big[G_2 \left ( f -
{k}/{T} \right)\big]= g_0 \cdot T \hspace{0.05cm},
+
{k}/{T} \right)\big]= g_0 \cdot T \hspace{0.05cm},$$
\hspace{0.5cm}\sum \limits_{\it k = -\infty}^{+\infty} {\rm Im}\left[G_2 \big ( f -
+
:$$\sum \limits_{\it k = -\infty}^{+\infty} {\rm Im}\left[G_2 \big ( f -
 
{k}/{T} \right)\big]= 0.$$
 
{k}/{T} \right)\big]= 0.$$
*Beim Imaginärteil heben sich die jeweils gleich schraffierten Anteile, die jeweils um &nbsp;$2/T$&nbsp; auseinander liegen, auf.
+
*In the imaginary part,&nbsp; the respective equally shaded parts,&nbsp; each &nbsp;$2/T$&nbsp; apart,&nbsp; cancels out.
* Die Angabe des dazugehörigen Nyquistimpulses &nbsp;$g_2(t)$&nbsp; ist allerdings sehr kompliziert.}}
+
* However,&nbsp; the specification of the corresponding Nyquist pulse &nbsp;$g_2(t)$&nbsp; is very complicated.}}
  
  
== Beweis des ersten Nyquistkriteriums ==
+
== Proof of the first Nyquist criterion ==
 
<br>
 
<br>
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
'''(1)''' &nbsp; Wir gehen von der ersten Nyquistbedingung im Zeitbereich aus:
+
'''(1)''' &nbsp; We start from the first Nyquist condition in the time domain:
 
:$$g_{\hspace{0.05cm}\rm Nyq}(\nu
 
:$$g_{\hspace{0.05cm}\rm Nyq}(\nu
 
T)  =  \left\{ \begin{array}{c} g_0  \\
 
T)  =  \left\{ \begin{array}{c} g_0  \\
 
  0 \\  \end{array} \right.\quad
 
  0 \\  \end{array} \right.\quad
\begin{array}{*{1}c} {\rm{f\ddot{u}r} }
+
\begin{array}{*{1}c} {\rm{for} }
\\  {\rm{f\ddot{u}r} }  \\ \end{array}\begin{array}{*{20}c}
+
\\  {\rm{for} }  \\ \end{array}\begin{array}{*{20}c}
 
\nu = 0 \hspace{0.05cm}, \\
 
\nu = 0 \hspace{0.05cm}, \\
 
\nu \ne 0  \hspace{0.1cm}.  \\
 
\nu \ne 0  \hspace{0.1cm}.  \\
 
\end{array}$$
 
\end{array}$$
'''(2)''' &nbsp; Aus dem zweiten Fourierintegral erhält man somit für &nbsp;$\nu \ne 0$:
+
'''(2)''' &nbsp; Thus,&nbsp; from the second Fourier integral,&nbsp; we obtain for &nbsp;$\nu \ne 0$:
 
:$$g_{\hspace{0.05cm}\rm Nyq}(\nu
 
:$$g_{\hspace{0.05cm}\rm Nyq}(\nu
 
T)  =  \int_{-\infty}^{+\infty}G_{\rm Nyq}(f) \cdot {\rm
 
T)  =  \int_{-\infty}^{+\infty}G_{\rm Nyq}(f) \cdot {\rm
 
e}^{ \hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi f \hspace{0.05cm}\nu
 
e}^{ \hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi f \hspace{0.05cm}\nu
 
\hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$
 
\hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$
'''(3)''' &nbsp; Zerlegt man das Fourierintegral in Teilintegrale der Breite &nbsp;$1/T$, so lauten die Bedingungsgleichungen:
+
'''(3)''' &nbsp; Decomposing the Fourier integral into partial integrals of width &nbsp;$1/T$,&nbsp; the conditional equations are:
 
:$$\sum_{k = -\infty}^{+\infty}  \hspace{0.2cm} \int_{(k-1/2)/T}^{(k+1/2)/T}G_{\rm Nyq}(f) \cdot {\rm
 
:$$\sum_{k = -\infty}^{+\infty}  \hspace{0.2cm} \int_{(k-1/2)/T}^{(k+1/2)/T}G_{\rm Nyq}(f) \cdot {\rm
 
e}^{ \hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi f \hspace{0.05cm}\nu
 
e}^{ \hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi f \hspace{0.05cm}\nu
 
\hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$
 
\hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$
'''(4)''' &nbsp; Mit der Substitution &nbsp;$f\hspace{0.08cm}' = f + k/T$&nbsp; folgt daraus:
+
'''(4)''' &nbsp; With the substitution &nbsp;$f\hspace{0.08cm}' = f + k/T$&nbsp; it follows:
 
:$$\sum_{k = -\infty}^{+\infty}  \hspace{0.2cm} \int_{-1/(2T)}^{1/(2T)}G_{\rm Nyq}(f\hspace{0.08cm}' -
 
:$$\sum_{k = -\infty}^{+\infty}  \hspace{0.2cm} \int_{-1/(2T)}^{1/(2T)}G_{\rm Nyq}(f\hspace{0.08cm}' -
 
\frac{k}{T} ) \cdot {\rm e}^{\hspace{0.05cm}{\rm j}
 
\frac{k}{T} ) \cdot {\rm e}^{\hspace{0.05cm}{\rm j}
Line 110: Line 108:
 
k/T) \hspace{0.05cm} \cdot \hspace{0.05cm}\nu
 
k/T) \hspace{0.05cm} \cdot \hspace{0.05cm}\nu
 
\hspace{0.05cm}T}\,{\rm d} f \hspace{0.08cm}' = 0 \hspace{0.05cm}.$$
 
\hspace{0.05cm}T}\,{\rm d} f \hspace{0.08cm}' = 0 \hspace{0.05cm}.$$
'''(5)''' &nbsp; Für alle ganzzahligen Werte von &nbsp;$k$&nbsp; und &nbsp;$\nu$&nbsp; gilt:
+
'''(5)''' &nbsp; For all integer values of &nbsp;$k$&nbsp; and &nbsp;$\nu$&nbsp; holds:
 
:$${\rm e}^{ - {\rm j} \hspace{0.05cm}2 \pi
 
:$${\rm e}^{ - {\rm j} \hspace{0.05cm}2 \pi
 
\hspace{0.05cm} k \hspace{0.05cm} \nu } = 1
 
\hspace{0.05cm} k \hspace{0.05cm} \nu } = 1
Line 117: Line 115:
 
\hspace{0.02cm}f\hspace{0.08cm}' \hspace{0.02cm} \nu \hspace{0.05cm}T}\,{\rm d} f
 
\hspace{0.02cm}f\hspace{0.08cm}' \hspace{0.02cm} \nu \hspace{0.05cm}T}\,{\rm d} f
 
\hspace{0.08cm}' = 0 \hspace{0.05cm}.$$
 
\hspace{0.08cm}' = 0 \hspace{0.05cm}.$$
'''(6)''' &nbsp; Durch Vertauschen von Summation und Integration sowie Umbenennen von  &nbsp;$f\hspace{0.08cm}'$&nbsp;  in &nbsp;$f$&nbsp; folgt weiter:
+
'''(6)''' &nbsp; Swapping summation and integration and renaming &nbsp;$f\hspace{0.08cm}'$&nbsp;  to &nbsp;$f$,&nbsp; it further follows:
 
:$$\int_{-1/(2T)}^{1/(2T)}\hspace{0.2cm} \sum_{k = - \infty}^{+\infty} G_{\rm Nyq}(f -
 
:$$\int_{-1/(2T)}^{1/(2T)}\hspace{0.2cm} \sum_{k = - \infty}^{+\infty} G_{\rm Nyq}(f -
 
\frac{k}{T} ) \cdot {\rm e}^{ {\rm j} \hspace{0.05cm}2 \pi
 
\frac{k}{T} ) \cdot {\rm e}^{ {\rm j} \hspace{0.05cm}2 \pi
 
\hspace{0.02cm}f \hspace{0.02cm} \nu \hspace{0.05cm}T}\,{\rm d} f
 
\hspace{0.02cm}f \hspace{0.02cm} \nu \hspace{0.05cm}T}\,{\rm d} f
 
  = 0 \hspace{0.05cm}.$$
 
  = 0 \hspace{0.05cm}.$$
'''(7)''' &nbsp; Diese Forderung ist für alle &nbsp;$\nu \ne 0$&nbsp; nur dann zu erfüllen, wenn die unendliche Summe unabhängig von &nbsp;$f$&nbsp; ist, also einen konstanten Wert besitzt:
+
'''(7)''' &nbsp; This requirement can be satisfied for all &nbsp;$\nu \ne 0$&nbsp; only if the infinite sum is independent of &nbsp;$f$,&nbsp; i.e.,&nbsp; has a constant value:
 
:$$\sum_{k = -\infty}^{+\infty} G_{\rm Nyq}(f -
 
:$$\sum_{k = -\infty}^{+\infty} G_{\rm Nyq}(f -
 
\frac{k}{T} ) =  K_{\rm Nyq} \hspace{0.05cm}.$$
 
\frac{k}{T} ) =  K_{\rm Nyq} \hspace{0.05cm}.$$
'''(8)''' &nbsp; Aus der vorletzten Gleichung erhält man gleichzeitig für &nbsp;$\nu = 0$:
+
'''(8)''' &nbsp; From the penultimate equation,&nbsp; we obtain simultaneously for &nbsp;$\nu = 0$:
 
:$$\int_{-1/(2T)}^{1/(2T)}\hspace{0.2cm} \sum_{k = -\infty}^{+\infty} G_{\rm Nyq}(f -
 
:$$\int_{-1/(2T)}^{1/(2T)}\hspace{0.2cm} \sum_{k = -\infty}^{+\infty} G_{\rm Nyq}(f -
 
\frac{k}{T} ) \,{\rm d} f
 
\frac{k}{T} ) \,{\rm d} f
  = K_{\rm Nyq} \cdot \frac{1}{T} = g_0 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}K_{\rm Nyq}  = g_0 \cdot T \hspace{0.05cm}.$$}}
+
  = K_{\rm Nyq} \cdot \frac{1}{T} = g_0 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}K_{\rm Nyq}  = g_0 \cdot T \hspace{0.05cm}.$$
 +
<div align="right">'''q.e.d.'''</div>}}
  
  
== 1/T–Nyquistspektren==
+
== 1/T Nyquist spectra==
 
<br>
 
<br>
Besondere Bedeutung für die Digitalsignalübertragung haben solche Nyquistspektren, die auf den Frequenzbereich &nbsp;$-1/T \le  f \le +1/T$&nbsp; beschränkt und zusammenhängend sind. Die Grafik zeigt mit der Trapez&ndash;Charakteristik und der Cosinus&ndash;Rolloff&ndash;Charakteristik zwei diesbezügliche Varianten.
+
Nyquist spectra which are limited to the frequency range &nbsp;$-1/T \le  f \le +1/T$&nbsp; and are coherent,&nbsp; have a particular importance for digital signal transmission.
 
 
[[File:P_ID1274__Dig_T_1_3_S3a_v1.png|center|frame|$1/T$-Nyquistspektren|class=fit]]
 
  
Für beide Nyquistspektren gilt in gleicher Weise:
+
The diagram shows the&nbsp; "trapezoidal characteristic"&nbsp; and the&nbsp; "cosine rolloff characteristic",&nbsp; which are two variants in this respect.
*Der Flankenabfall erfolgt zwischen den zwei Eckfrequenzen &nbsp;$f_1$&nbsp; und &nbsp;$f_2$&nbsp; punktsymmetrisch um die '''Nyquistfrequenz''' &nbsp;$f_{\rm Nyq} = (f_1+f_2)/2$. Das heißt, dass für &nbsp;$0 \le f \le f_{\rm Nyq}$&nbsp; gilt:
+
The same applies to both Nyquist spectra:
 +
*The rolloff occurs between the two corner frequencies &nbsp;$f_1$&nbsp; and &nbsp;$f_2$&nbsp; point-symmetrically about the&nbsp; '''Nyquist frequency''' &nbsp;$f_{\rm Nyq} = (f_1+f_2)/2$.&nbsp; <br>That is,&nbsp; for &nbsp;$0 \le f \le f_{\rm Nyq}$:&nbsp;
 
:$$G_{\rm Nyq}(f_{\rm Nyq}+f) + G_{\rm Nyq}(f_{\rm Nyq}-f) = g_0 \cdot T \hspace{0.05cm}.$$
 
:$$G_{\rm Nyq}(f_{\rm Nyq}+f) + G_{\rm Nyq}(f_{\rm Nyq}-f) = g_0 \cdot T \hspace{0.05cm}.$$
*$G_{\rm Nyq}(f)$&nbsp; ist für alle Frequenzen &nbsp;$|f| \le f_1$&nbsp; konstant gleich &nbsp;$g_0 \cdot T$&nbsp; und für &nbsp;$|f| \ge f_2$&nbsp; identisch Null. Im Bereich zwischen &nbsp;$f_1$&nbsp; und &nbsp;$f_2$&nbsp; gilt:
+
*For all frequencies &nbsp;$|f| \le f_1$,&nbsp; the function&nbsp; $G_{\rm Nyq}(f)$&nbsp; is constantly equal to &nbsp;$g_0 \cdot T$&nbsp; and for &nbsp;$|f| \ge f_2$&nbsp; it is identically zero.
 +
[[File:EN_Dig_T_1_3_S3a_vers2.png|right|frame|$1/T$&nbsp; Nyquist spectra|class=fit]]
 +
*In the range between &nbsp;$f_1$&nbsp; and &nbsp;$f_2$&nbsp; holds:
 
:$$\frac{G_{\rm Nyq}(f)}{g_0 \cdot T }  =  \left\{ \begin{array}{c} \frac{f_2 - |f|}{f_2 -f_1 }
 
:$$\frac{G_{\rm Nyq}(f)}{g_0 \cdot T }  =  \left\{ \begin{array}{c} \frac{f_2 - |f|}{f_2 -f_1 }
 
  \\ \\
 
  \\ \\
 
  \cos^2( \frac{\pi}{2}\cdot \frac{f_2 - |f|}{f_2 -f_1 }) \\  \end{array} \right.\quad
 
  \cos^2( \frac{\pi}{2}\cdot \frac{f_2 - |f|}{f_2 -f_1 }) \\  \end{array} \right.\quad
\begin{array}{*{1}c} {\rm{beim \hspace{0.15cm}Trapez}\hspace{0.05cm},}
+
\begin{array}{*{1}c} {\rm{at \hspace{0.15cm}trapezoidal}\hspace{0.05cm},}
\\ \\ {\rm{\rm{beim \hspace{0.15cm}Cosinus-Rolloff}}\hspace{0.05cm}.}  \\ \end{array}$$
+
\\ \\ {\rm{\rm{at \hspace{0.15cm}cosine \hspace{0.15cm}rolloff}}\hspace{0.05cm}.}  \\ \end{array}$$
*Zur Parametrisierung der Flankensteilheit verwenden wir den '''Rolloff&ndash;Faktor''' &nbsp;$r$, der Werte zwischen &nbsp;$0$&nbsp; und &nbsp;$1$&nbsp; (einschließlich dieser Grenzen) annehmen kann:
+
*To parameterize the slope,&nbsp; we use the&nbsp; '''rolloff factor''' &nbsp;$r$,&nbsp; which can take values between &nbsp;$0$&nbsp; and &nbsp;$1$&nbsp; (including these limits):
 
:$$r = \frac{f_2 -f_1 }
 
:$$r = \frac{f_2 -f_1 }
 
{f_2 +f_1 } \hspace{0.05cm}.$$
 
{f_2 +f_1 } \hspace{0.05cm}.$$
*Für &nbsp;$r = 0$ &nbsp; &rArr; &nbsp; $f_1 = f_2 = f_{\rm Nyq}$&nbsp; ergibt sich das (grün&ndash;gepunktete) Rechteck-Nyquistspektrum.
+
:In the literature,&nbsp; the rolloff factor is sometimes referred to as &nbsp;$\alpha$&nbsp; ("alpha").
* Der Rolloff-Faktor &nbsp;$r = 1$ &nbsp; &rArr; &nbsp;  $f_1 = 0, \ f_2 = 2 f_{\rm Nyq}$&nbsp; steht für ein dreieckförmiges &nbsp;bzw.&nbsp; ein $\cos^2$&ndash;Spektrum &ndash; je nachdem, von welcher der beiden oben abgebildeten Grundstrukturen man ausgeht. Diese Frequenzverläufe sind jeweils rot&ndash;gestrichelt eingezeichnet.
+
 
 +
*For &nbsp;$r = 0$ &nbsp; &rArr; &nbsp; $f_1 = f_2 = f_{\rm Nyq}$&nbsp; we obtain in both cases the&nbsp; (green&ndash;dotted)&nbsp; rectangular Nyquist spectrum.
 +
* The rolloff factor &nbsp;$r = 1$ &nbsp; &rArr; &nbsp;  $f_1 = 0, \ f_2 = 2 f_{\rm Nyq}$&nbsp; stands
 +
#for the triangular spectrum
 +
#resp.&nbsp; the cosine-square spectrum,&nbsp;  
  
 +
:depending on which of the two basic structures shown above one assumes.&nbsp; These frequency curves are shown in red dashed lines.
  
''Hinweis:'' &nbsp; In der Literatur wird der Rolloff&ndash;Faktor auch oft mit &nbsp;$\alpha$&nbsp; (&bdquo;alpha&rdquo;) bezeichnet.
 
  
  
==Zeitbereichsberschreibung der 1/T–Nyquistspektren ==
+
 
 +
==Time domain description of the 1/T Nyquist spectra ==
 
<br>
 
<br>
Betrachten wir nun die Nyquistimpulse. Beim ''trapezförmigem Spektrum'' mit Rolloff&ndash;Faktor $r$ erhält man:
+
Let us now consider the Nyquist pulses.&nbsp; For the &nbsp;'''trapezoidal spectrum'''&nbsp; with rolloff factor &nbsp;$r$,&nbsp; we obtain:
:$$g_{_{\rm Trapez}} ( t )= g_0 \cdot {\rm si} \left ( \frac{\pi
+
:$$g_{_{\rm trapezoid}} ( t )= g_0 \cdot {\rm sinc} \left ( \frac{t}{T}\right)\cdot {\rm sinc} \left ( \frac{r \cdot
\cdot t}{T}\right)\cdot {\rm si} \left ( \frac{\pi \cdot r \cdot
+
t}{T}\right) \hspace{0.5cm}{\rm with }\hspace{0.5cm}{\rm sinc}(x) = {\rm sin}(\pi x)/(\pi x.$$
t}{T}\right) \hspace{0.5cm}{\rm mit }\hspace{0.5cm}{\rm si}(x) = {\rm sin}(x)/x .$$
+
In contrast,&nbsp; the Fourier inverse transform of the&nbsp; '''cosine rolloff spectrum'''&nbsp; (short:&nbsp; "CRO spectrum") yields:
Dagegen liefert die Fourierrücktransformation des ''Cosinus&ndash;Rolloff&ndash;Spektrums'' (kurz: CRO:&ndash;Spektrum):
+
:$$g_{_{\rm CRO}} ( t )= g_0 \cdot {\rm sinc} \left ( \frac{
:$$g_{_{\rm CRO}} ( t )= g_0 \cdot {\rm si} \left ( \frac{\pi \cdot
 
 
t}{T}\right)\cdot \frac{\cos(\pi \cdot r \cdot t/T)}{1 - (2 \cdot
 
t}{T}\right)\cdot \frac{\cos(\pi \cdot r \cdot t/T)}{1 - (2 \cdot
r \cdot t/T)^2 } \hspace{0.3cm}{\rm mit }\hspace{0.3cm}{\rm si}(x) = {\rm sin}(x)/x.$$
+
r \cdot t/T)^2 } \hspace{0.3cm}{\rm with }\hspace{0.3cm}{\rm sinc}(x) = {\rm sin}(\pi x)/(\pi x).$$
Diese beiden Nyquistimpulse kann man mit dem Interaktionsmodul [[Applets:Frequenzgang_und_Impulsantwort|Frequenzgang und Impulsantwort]] (mit der Einstellung $ \Delta \cdot f = 1$) betrachten und sich dabei den Einfluss des Rolloff&ndash;Faktors $r$ verdeutlichen.
+
These pulses can be viewed using the HTML5/JS applet &nbsp;[[Applets:Frequency_%26_Impulse_Responses|"Frequency & Impulse Responses"]]&nbsp; $($with setting &nbsp;$ \Delta \cdot f = 1)$,&nbsp; illustrating the influence of the rolloff factor &nbsp;$r$.&nbsp;
  
 +
The following upper diagram shows the Nyquist pulse with trapezoidal spectrum for different rolloff factors. Below is the corresponding time course for the cosine rolloff spectrum. One can see:
 +
[[File:EN_Dig_T_1_3_S3b_v2.png|right|frame|Nyquist pulses with trapezoidal and cosine rolloff spectrum|class=fit]]
 +
#The smaller the rolloff factor &nbsp;$r$,&nbsp; the slower the decay of the Nyquist pulse. This statement is true for both the trapezoidal and the cosine rolloff spectra.
 +
#In the limiting case &nbsp;$r \to 0$,&nbsp; both cases yield the rectangular Nyquist spectrum and the &nbsp;$\rm sinc$&ndash;shaped Nyquist pulse, &nbsp; which decays asymptotically with &nbsp;$1/t$&nbsp; (thin green curves).
 +
#For an average rolloff &nbsp;$(r \approx 0.5)$,&nbsp; the first overshoots are smaller for the trapezoidal spectrum than for the CRO spectrum,&nbsp; because here the Nyquist slope is flatter for a given &nbsp;$r$&nbsp; (blue curves).
 +
#With the rolloff factor &nbsp;$r = 1$,&nbsp; the trapezoid becomes a triangle in the frequency domain and the CRO spectrum becomes the&nbsp; "cosine&ndash;square spectrum".&nbsp; In the diagrams in the &nbsp;[[Digital_Signal_Transmission/Properties_of_Nyquist_Systems#1.2FT_Nyquist_spectra|"last section"]]&nbsp; these spectral functions are drawn in red.
 +
#With &nbsp;$r = 1$&nbsp; the asymptotically decay of the upper time function&nbsp; (according to the trapezoidal spectrum)&nbsp; occurs with &nbsp;$1/t^2$,&nbsp; the decay of the lower function&nbsp; (according to the CRO spectrum)&nbsp; with &nbsp;$1/t^3$.
 +
#This means: &nbsp; After a longer time,&nbsp; the CRO Nyquist pulse has settled better than the trapezoidal Nyquist pulse.
  
Die obere Grafik zeigt den Nyquistimpuls mit Trapezspektrum für verschiedene Rolloff&ndash;Faktoren. Unten ist der entsprechende Zeitverlauf für das Cosinus&ndash;Rolloff&ndash;Spektrum dargestellt. Man erkennt:
 
[[File:P_ID1276__Dig_T_1_3_S3b_v1.png|right|frame|Nyquistimpulse mit Trapez- und Cosinus-Rolloff-Spektrum|class=fit]]
 
*Je kleiner der Rolloff&ndash;Faktor $r$ ist, desto langsamer erfolgt der Abfall des Nyquistimpulses. Diese Aussage trifft sowohl für das Trapez&ndash; als auch für das Cosinus&ndash;Rolloff&ndash;Spektrum zu.
 
*Im Grenzfall $r \to 0$ ergibt sich in beiden Fällen das rechteckförmige Nyquistspektrum und der $\rm si$&ndash;förmige Nyquistimpuls, der asymptotisch mit $1/t$ abklingt  (dünne grüne Kurven).
 
*Bei einem mittleren Rolloff $(r \approx 0.5)$ sind die ersten Überschwinger beim Trapezspektrum geringer als beim CRO&ndash;Spektrum, da bei gegebenem $r$ die Nyquistflanke flacher verläuft (blaue Kurven).
 
*Mit dem Rolloff&ndash;Faktor $r = 1$ wird im Frequenzbereich aus dem Trapez ein Dreieck und aus dem CRO&ndash;Spektrum das Cosinus&ndash;Quadrat&ndash;Spektrum. In den Grafiken auf der [[Digitalsignalübertragung/Eigenschaften_von_Nyquistsystemen#1.2FT.E2.80.93Nyquistspektren|letzten Seite]] sind diese Spektralfunktionen rot gezeichnet.
 
*Mit $r = 1$ erfolgt der asymptotische Abfall der oberen Zeitfunktion (gemäß dem Trapezspektrum) mit $1/t^2$ und der Abfall der unteren Zeitfunktion (gemäß dem CRO&ndash;Spektrum) mit $1/t^3$ &nbsp; &rArr; &nbsp; nach längerer Zeit ist der CRO&ndash;Nyquistimpuls besser eingeschwungen als  der Trapez&ndash;Nyquistimpuls .
 
  
 +
== Second Nyquist criterion==
 +
<br>
 +
Before the exact mathematical definition,&nbsp; the significance of the&nbsp; '''second Nyquist criterion'''&nbsp; for the evaluation of a digital system is illustrated by means of diagrams. The graphic shows three examples of Nyquist systems,&nbsp; in each case:
 +
*at the top,&nbsp; the Nyquist spectrum &nbsp;$G_d(f)$,
 +
*below the corresponding&nbsp; "eye diagram"&nbsp; referring to the &nbsp;[[Digital_Signal_Transmission/Error_Probability_with_Intersymbol_Interference#Definition_and_statements_of_the_eye_diagram|"third main chapter"]].
  
== Zweites Nyquistkriterium==
+
[[File:EN_Dig_T_1_3_S4_v3.png|right|frame|Clarification of first and second Nyquist criterion]]
<br>
+
 
Vor der exakten mathematischen Definition soll anhand von Grafiken veranschaulicht werden, welche Bedeutung das ''zweite Nyquistkriterium'' zur Bewertung eines Digitalsystems besitzt. In der Grafik sind für drei Beispiele von Nyquistsystemen jeweils  dargestellt:
+
 
*oben das Nyquistspektrum $G_d(f)$,
+
$\text{Interpretation:}$
*unten das dazugehörige Augendiagramm im Vorgriff auf das [[Digitalsignalübertragung/Fehlerwahrscheinlichkeit_unter_Berücksichtigung_von_Impulsinterferenzen#Definition_und_Aussagen_des_Augendiagramms|dritte Hauptkapitel]].
+
*The diagram on the left shows the eye diagram of a Nyquist system with cosine rolloff characteristic,&nbsp; where the rolloff factor &nbsp;$r= 0.5$&nbsp; was chosen.&nbsp; Since the first Nyquist criterion is fulfilled here&nbsp; (there is point symmetry around the Nyquist frequency &nbsp;$f_{\rm Nyq}$,&nbsp; the  vertical eye opening at time &nbsp;$t = 0$&nbsp; is &nbsp;$2 \cdot g_d(0)$.&nbsp; All eye lines pass  at time &nbsp;$t = 0$&nbsp; through one of the two points marked in red &nbsp; &rArr;  &nbsp; the eye is vertically maximally open.
 +
 
 +
 
 +
*The middle spectrum does not show any symmetry with respect to the rolloff,&nbsp; so that the first Nyquist criterion is not fulfilled here &ndash; in contrast to the second one.&nbsp; All eyelines here intersect the time axis at the same times&nbsp; (marked by the green dots),&nbsp; which facilitates,&nbsp; for example,&nbsp; clock recovery by means of a&nbsp; $\rm PLL$&nbsp; ("Phase-Locked Loop").&nbsp; When the second Nyquist criterion is met,&nbsp; the horizontal eye opening is maximally equal to the symbol duration $T$ &nbsp; &rArr;  &nbsp; the eye is maximally open horizontally.
  
  
[[File:P_ID1277__Dig_T_1_3_S4_v1.png|center|frame|Zur Verdeutlichung von erstem und  zweitem Nyquistkriterium]]
+
*The right eye diagram illustrates that for the CRO spectrum with &nbsp;$r = 1$,&nbsp; both the first and second Nyquist criteria are satisfied.&nbsp; Here,&nbsp; the Nyquist pulse
''Interpretation:''
+
:$$g_d ( t )= g_0 \cdot \frac{\pi }{4}\cdot {\rm sinc} \left (
*Die linke Grafik zeigt das Augendiagramm eines Nyquistsystems mit Cosinus&ndash;Rolloff&ndash;Charakteristik, wobei der Rolloff&ndash;Faktor $r= 0.5$ gewählt wurde. Da hier das erste Nyquistkriterium  erfüllt ist (es besteht eine Punktsymmetrie um die Nyquistfrequenz $f_{\rm Nyq}$, ergibt sich für die vertikale Augenöffnung zum Zeitpunkt $t = 0$ der größtmögliche Wert $2 \cdot g_d(0)$. Alle Augenlinien gehen zum Zeitpunkt $t = 0$  durch einen der beiden rot markierten Punkte &nbsp; &rArr;  &nbsp; das Auge ist vertikal maximal geöffnet.
+
\frac{ t}{T}\right)\cdot \left [ {\rm sinc}
*Das mittlere Spektrum weist keine Symmetrie bezüglich des Flankenabfalls auf, so dass hier das erste Nyquistkriterium nicht erfüllt ist &ndash; im Gegensatz zum zweiten. Alle Augenlinien schneiden hier die Zeitachse zu den selben Zeiten (markiert durch die grünen  Punkte), was beispielsweise die Taktwiedergewinnung mittels einer PLL (<i>Phase-Locked Loop</i>) erleichtert. Bei Erfüllung des zweiten Nyquistkriteriums ist die horizontale Augenöffnung maximal gleich der Symboldauer $T$ &nbsp; &rArr;  &nbsp; das Auge ist horizontal maximal geöffnet.
+
(\frac{t}{T} + \frac{1}{2}) + {\rm sinc} (\frac{t}{T} -
*Das rechte Augendiagrammm verdeutlicht, dass beim CRO&ndash;Spektrum mit $r = 1$ sowohl das erste als auch das zweite Nyquistkriterium erfüllt werden. Der Nyquistimpuls
 
:$$g_d ( t )= g_0 \cdot \frac{\pi }{4}\cdot {\rm si} \left (
 
\frac{\pi \cdot t}{T}\right)\cdot \left [ {\rm si}(\pi \cdot
 
(\frac{t}{T} + \frac{1}{2}) + {\rm si}(\pi \cdot (\frac{t}{T} -
 
 
\frac{1}{2})\right]$$
 
\frac{1}{2})\right]$$
:weist hier die erforderlichen Nulldurchgänge bei $t = \pm T$, $t = \pm 1.5T$, $t = \pm 2T$, $t = \pm 2.5T$,  ... auf, nicht jedoch bei $t = \pm 0.5T$. Die Impulsamplitude ist $g_d(t = 0) = g_0$. &nbsp; &nbsp;''Hinweis:'' Kein anderer Impuls erfüllt gleichzeitig das erste und das zweite Nyquistkriterium.
+
:exhibits the required zero crossings at &nbsp;$t = \pm T$, &nbsp;$t = \pm 1.5T$, &nbsp;$t = \pm 2T$, &nbsp;$t = \pm 2.5T$,  ... but not at &nbsp;$t = \pm 0.5T$. The pulse amplitude is &nbsp;$g_d(t = 0) = g_0$. &nbsp; &nbsp;<br><u>Note</u>: &nbsp; '''No other pulse satisfies both the first and second Nyquist criteria simultaneously'''.
  
  
  
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
$\text{Zusammenfassung der Nyquistkriterien:}$<br>
+
$\text{Summary of Nyquist criteria:}$<br><br>
'''(1)''' &nbsp; In Erinnerung an den Physiker [https://de.wikipedia.org/wiki/Harry_Nyquist Harry Nyquist]  bezeichnen wir einen Detektionsgrundimpuls $g_d( t)$ mit den Eigenschaften
+
'''(1)''' &nbsp; In memory of the physicist &nbsp;[https://en.wikipedia.org/wiki/Harry_Nyquist "Harry Nyquist"]&nbsp; we denote a basic detection pulse  &nbsp;$g_d( t)$&nbsp; with the properties
:$$g_d ( t= 0) \ne  0, \hspace{1cm} g_d ( t)= 0 \hspace{0.3cm}{\rm{f\ddot{u}r} }\hspace{0.3cm}
+
::$$g_d ( t= 0) \ne  0, \hspace{1cm} g_d ( t)= 0 \hspace{0.3cm}{\rm{for} }\hspace{0.3cm}
 
t = \pm T, \pm 2T,\pm 3T,\hspace{0.05cm}\text{...}$$
 
t = \pm T, \pm 2T,\pm 3T,\hspace{0.05cm}\text{...}$$
:als Nyquistimpuls $g_{\hspace{0.05cm}\rm Nyq-1}(t)$. Dieser erfüllt das erste Nyquistkriterium und führt zur maximalen vertikalen Augenöffnung.
+
:as the&nbsp; '''Nyquist&ndash;1 pulse''' &nbsp;$g_{\hspace{0.05cm}\rm Nyq-1}(t)$.&nbsp; This satisfies the first Nyquist criterion and leads to the maximum vertical eye opening.
'''(2)''' &nbsp; Ein Impuls $g_{\hspace{0.05cm}\rm Nyq-2}(t)$, der das zweite Nyquistkriterium erfüllt, muss Nulldurchgänge bei $t = \pm 1.5T$, $t = \pm 2.5T$, ... besitzen:
+
'''(2)''' &nbsp; A basic detection pulse  &nbsp;$g_d( t)$&nbsp; satisfying the second Nyquist criterion must have zero crossings at &nbsp;$t = \pm 1.5T$, &nbsp;$t = \pm 2.5T$, ...&nbsp; have:
:$$g_d ( t= 0.5) \ne  0, \hspace{0.8cm} g_d ( t)= 0 \hspace{0.3cm}{\rm{f\ddot{u}r} }\hspace{0.3cm}
+
::$$g_d ( t= 0.5) \ne  0, \hspace{0.8cm} g_d ( t)= 0 \hspace{0.3cm}{\rm{for} }\hspace{0.3cm}
t = \pm 1.5T, \pm 2.5T,\pm 3.5T,\hspace{0.05cm}\text{...}$$
+
t = \pm 1.5T, \ \pm 2.5T,\ \pm 3.5T,\hspace{0.05cm}\text{...}$$
:Ein solcher Nyquist&ndash;2&ndash;Impuls führt zur maximalen horizontalen Augenöffnung.
+
:Such a&nbsp; '''Nyquist&ndash;2 pulse'''&nbsp; leads to the maximum horizontal eye opening.
'''(3)''' &nbsp; Ein Nyquist&ndash;2&ndash;Impuls kann immer als Summe zweier um $t = \pm T/2$ verschobener Nyquist&ndash;1&ndash;Impulse dargestellt werden:
+
'''(3)''' &nbsp; A Nyquist&ndash;2 pulse can always be represented as the sum of two Nyquist&ndash;1 pulses shifted by &nbsp;$t = \pm T/2$:&nbsp;  
:$$g_{\rm Nyq-2} ( t )= g_{\rm Nyq-1} ( t +T/2)+g_{\rm Nyq-1} ( t -T/2)\hspace{0.05cm}.$$
+
::$$g_{\rm Nyq-2} ( t )= g_{\rm Nyq-1} ( t +T/2)+g_{\rm Nyq-1} ( t -T/2)\hspace{0.05cm}.$$
'''(4)''' &nbsp; Im Frequenzbereich lautet das zweite Nyquistkriterium (siehe [ST85] <ref>Söder, G.; Tröndle, K.: ''Digitale Übertragungssysteme - Theorie, Optimierung & Dimensionierung der Basisbandsysteme.'' Berlin Heidelberg: Springer, 1985.</ref>):
+
'''(4)''' &nbsp; In the frequency domain,&nbsp; the second Nyquist criterion&nbsp; (see [TS87] <ref>Tröndle, K.; Söder, G.:&nbsp; Optimization of Digital Transmission Systems.&nbsp; Boston London:&nbsp; Artech House, 1987.</ref>) is:
:$$\sum_{k = -\infty}^{+\infty} \frac {G_d \left ( f -k/T
+
::$$\sum_{k = -\infty}^{+\infty} \frac {G_d \left ( f -k/T
 
\right)}{\cos(\pi \cdot f \cdot T - k \cdot \pi)}= {\rm const.}$$}}
 
\right)}{\cos(\pi \cdot f \cdot T - k \cdot \pi)}= {\rm const.}$$}}
  
  
 
{{GraueBox|TEXT=   
 
{{GraueBox|TEXT=   
$\text{Beispiel 3:}$&nbsp; Ausgehend vom Nyquist&ndash;1&ndash;Impuls $g_{\rm Nyq-1}( t )= g_0 \cdot {\rm si}(\pi \cdot t/T)$ lautet der dazugehörige Nyquist&ndash;2&ndash;Impuls:
+
$\text{Example 3:}$&nbsp; Starting from the Nyquist&ndash;1 pulse &nbsp;$g_{\rm Nyq-1}( t )= g_0 \cdot {\rm sinc}(t/T)$&nbsp; the corresponding Nyquist&ndash;2 pulse is:
:$$g_{\rm Nyq-2}( t ) = g_0 \cdot  \left [ {\rm si}(\pi \cdot \frac{t + T/2}{T})  + {\rm si}(\pi \cdot \frac{t- T/2}{T}) \right] =\frac{2 \cdot g_0}{\pi} \cdot \frac{\cos(\pi \cdot t/T)}{1 - (2 \cdot t/T)^2}\hspace{0.05cm}.$$
+
:$$g_{\rm Nyq-2}( t ) = g_0 \cdot  \left [ {\rm sinc}( \frac{t + T/2}{T})  + {\rm sinc}( \frac{t- T/2}{T}) \right] =\frac{2 \cdot g_0}{\pi} \cdot \frac{\cos(\pi \cdot t/T)}{1 - (2 \cdot t/T)^2}\hspace{0.05cm}.$$
Aufgrund der Begrenzung des Spektrums $G_{\rm Nyq-1}( f)$ auf den Bereich$\vert f \vert \le f_{\rm Nyq} = 1/(2T)$ beschränkt sich in obiger Gleichung die Summe auf den Term mit $k = 0$ und man erhält:
+
*Due to the limitation of the spectrum &nbsp;$G_{\rm Nyq-1}( f)$&nbsp; to the range &nbsp;$\vert f \vert \le f_{\rm Nyq} = 1/(2T)$,&nbsp; the sum in equation&nbsp; '''(4)'''&nbsp; is limited to the term with &nbsp;$k = 0$,&nbsp; and we obtain:
 
:$$G_{\rm Nyq-2}(f)  =  \left\{ \begin{array}{c} g_0 \cdot T  \cdot \cos(\pi/2 \cdot f/f_{\rm Nyq}) \\
 
:$$G_{\rm Nyq-2}(f)  =  \left\{ \begin{array}{c} g_0 \cdot T  \cdot \cos(\pi/2 \cdot f/f_{\rm Nyq}) \\
 
   \\ 0 \\\end{array} \right.\quad
 
   \\ 0 \\\end{array} \right.\quad
\begin{array}{*{1}c} {\rm{f\ddot{u}r} }\hspace{0.15cm} \vert f \vert < f_{\rm
+
\begin{array}{*{1}c} {\rm{for} }\hspace{0.15cm} \vert f \vert < f_{\rm
 
Nyq}\hspace{0.05cm},
 
Nyq}\hspace{0.05cm},
\\    \\ {\rm{sonst} }\hspace{0.05cm}. \\
+
\\    \\ {\rm{otherwise} }\hspace{0.05cm}. \\
 
\end{array}$$
 
\end{array}$$
*Dieser Frequenzverlauf und das dazugehörige Augendiagramm ist in in der mittleren  Spalte der obigen  Grafik skizziert.  
+
*This frequency response and the corresponding eye diagram is sketched in the middle column of the above diagram.
*Man erkennt deutlich die Erfüllung des zweiten Nyquistkriteriums.}}
+
*From the bottom diagram, one can clearly see the fulfillment of the second Nyquist criterion.}}
  
  
  
== Aufgaben zum Kapitel ==
+
== Exercises for the chapter ==
 
<br>
 
<br>
[[Aufgaben:1.4_Nyquistkriterien|Aufgabe 1.4: Nyquistkriterien]]
+
[[Aufgaben:Exercise_1.4:_Nyquist_Criteria|Exercise 1.4: Nyquist Criteria]]
  
[[Aufgaben:1.4Z_Komplexes_Nyquistspektrum|Aufgabe 1.4Z: Komplexes Nyquistspektrum]]
+
[[Aufgaben:Exercise_1.4Z:_Complex_Nyquist_Spectrum|Exercise 1.4Z: Complex Nyquist Spectrum]]
  
[[Aufgaben:1.5_Cosinus-Quadrat-Spektrum|Aufgabe 1.5: Cosinus-Quadrat-Spektrum]]
+
[[Aufgaben:Exercise_1.5:_Cosine-Square_Spectrum|Exercise 1.5: Cosine-Square Spectrum]]
  
==Quellenverzeichnis==
+
==References==
  
 
<references/>
 
<references/>

Latest revision as of 00:20, 13 November 2022


First Nyquist criterion in the time domain


For the entire first main chapter it was assumed that the detection of a symbol should not be affected by neighboring pulses.  This is achieved by the detection of the signal

$$d(t) = d_{\rm S}(t) = \sum \limits_{\it (\nu)} a_\nu \cdot g_d ( t - \nu T)$$

at the detection times  $(\nu \cdot T)$  whenever the basic detection pulse  $g_d(t)$


For the sake of simplicity,  the noise component of the detection signal is assumed to be negligibly small in the following   ⇒   $d_{\rm N}(t) =0$.

$\text{Definition:}$  One denotes a basic detection pulse with the properties

$$g_d ( t = \nu T)= 0 \hspace{0.3cm}{\rm{for} }\hspace{0.3cm} \nu = \pm 1, \pm 2,\pm 3,\hspace{0.05cm}\text{...}$$

as  Nyquist pulse  $g_{\hspace{0.05cm}\rm Nyq}(t)$,  named after the physicist  "Harry Nyquist".


Detection signal with Nyquist pulse shaping

$\text{Example 1:}$  The diagram shows the detection signal  $d(t)$  of such a Nyquist system.  Dotted in red are the  (weighted and shifted)  Nyquist pulses  $a_\nu \cdot g_{\hspace{0.05cm}\rm Nyq}(t -\nu \cdot T)$. 

Please note:

  • At the detection times hold   $d(\nu \cdot T) = a_\nu \cdot g_{\hspace{0.05cm}\rm Nyq}(0)$,  as shown by the blue circles and the green grid.
  • The trailing edge   ⇒   "trailers"  of preceding pulses  $(\nu < 0)$  as well as the rising edge   ⇒   "precursors"  of following pulses  $(\nu > 0)$  do not affect the detection of the symbol  $a_0$  in the Nyquist system.


It should be mentioned that this graph is valid for the basic detection pulse with trapezoidal spectrum and rolloff factor  $r = 0.5$:

$$g_{\hspace{0.05cm}\rm Nyq} ( t )= g_0 \cdot {\rm sinc} \left ( \frac{t}{T}\right)\cdot {\rm sinc} \left ( \frac{ t}{2 \cdot T}\right),$$

which has already been discussed in the section  "Trapezoidal low-pass filter"  of the book  "Linear Time Invariant Systems".


First Nyquist criterion in the frequency domain


"Harry Nyquist"  formulated the condition for detection without intersymbol interfering not only for the time domain,  but in 1928 he also gave the corresponding criterion in the frequency domain.

$\text{First Nyquist criterion:}$  If the spectrum  $G_d(f)$  of the basic detection pulse  $g_d(t)$  fulfills the condition

$$\sum \limits_{\it k = -\infty}^{+\infty} G_d \left ( f - {k}/{T} \right)= g_0 \cdot T = {\rm const.} \hspace{0.05cm}, $$

then  $g_d(t)$  is a Nyquist pulse

  • with equidistant zero crossings at the times  $\nu \cdot T$  for  $\nu \ne 0$  and
  • the amplitude  $g_d(t = 0) = g_0$.


$\text{Note}$:  The proof follows in the  "next section".


$\text{Example 2:}$  Sketched are two Nyquist spectra  $G_1(f)$  and  $G_2(f)$, which are composed of rectangular and triangular segments:

The purely real spectrum sketched  $G_1(f)$  on the left satisfies the condition formulated above with the smallest possible bandwidth:

Illustration of the first Nyquist criterion
$$G_1(f) \hspace{-0.05cm}=\hspace{-0.05cm} \left\{ \begin{array}{c} g_0 \cdot T \\ 0 \\ \end{array} \right. \begin{array}{*{1}c} \text{for} \\ \text{for} \\ \end{array}\begin{array}{*{20}c} \vert f \vert \hspace{-0.08cm}<\hspace{-0.08cm} {1}/(2T), \\ \vert f \vert \hspace{-0.08cm}>\hspace{-0.08cm} {1}/(2T), \\ \end{array}$$

But the associated Nyquist pulse  $g_1(t) = g_0 \cdot {\rm sinc}(t/T)$  decays very slowly, asymptotically with  $1/t$.


The real part of the spectrum  $G_2(f)$  shown on the upper right was constructed from the rectangular spectrum by $G_1(f)$  by shifting parts of them by  $1/T$  to the right or to the left. 

  • $G_2(f)$  is also a Nyquist spectrum because of
$$\sum \limits_{\it k = -\infty}^{+\infty} {\rm Re}\big[G_2 \left ( f - {k}/{T} \right)\big]= g_0 \cdot T \hspace{0.05cm},$$
$$\sum \limits_{\it k = -\infty}^{+\infty} {\rm Im}\left[G_2 \big ( f - {k}/{T} \right)\big]= 0.$$
  • In the imaginary part,  the respective equally shaded parts,  each  $2/T$  apart,  cancels out.
  • However,  the specification of the corresponding Nyquist pulse  $g_2(t)$  is very complicated.


Proof of the first Nyquist criterion


(1)   We start from the first Nyquist condition in the time domain:

$$g_{\hspace{0.05cm}\rm Nyq}(\nu T) = \left\{ \begin{array}{c} g_0 \\ 0 \\ \end{array} \right.\quad \begin{array}{*{1}c} {\rm{for} } \\ {\rm{for} } \\ \end{array}\begin{array}{*{20}c} \nu = 0 \hspace{0.05cm}, \\ \nu \ne 0 \hspace{0.1cm}. \\ \end{array}$$

(2)   Thus,  from the second Fourier integral,  we obtain for  $\nu \ne 0$:

$$g_{\hspace{0.05cm}\rm Nyq}(\nu T) = \int_{-\infty}^{+\infty}G_{\rm Nyq}(f) \cdot {\rm e}^{ \hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi f \hspace{0.05cm}\nu \hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$

(3)   Decomposing the Fourier integral into partial integrals of width  $1/T$,  the conditional equations are:

$$\sum_{k = -\infty}^{+\infty} \hspace{0.2cm} \int_{(k-1/2)/T}^{(k+1/2)/T}G_{\rm Nyq}(f) \cdot {\rm e}^{ \hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi f \hspace{0.05cm}\nu \hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$

(4)   With the substitution  $f\hspace{0.08cm}' = f + k/T$  it follows:

$$\sum_{k = -\infty}^{+\infty} \hspace{0.2cm} \int_{-1/(2T)}^{1/(2T)}G_{\rm Nyq}(f\hspace{0.08cm}' - \frac{k}{T} ) \cdot {\rm e}^{\hspace{0.05cm}{\rm j} \hspace{0.05cm}2 \pi \hspace{0.05cm} \cdot \hspace{0.05cm} (f\hspace{0.08cm}'- k/T) \hspace{0.05cm} \cdot \hspace{0.05cm}\nu \hspace{0.05cm}T}\,{\rm d} f \hspace{0.08cm}' = 0 \hspace{0.05cm}.$$

(5)   For all integer values of  $k$  and  $\nu$  holds:

$${\rm e}^{ - {\rm j} \hspace{0.05cm}2 \pi \hspace{0.05cm} k \hspace{0.05cm} \nu } = 1 \hspace{0.4cm} \Rightarrow \hspace{0.4cm}\sum_{k = - \infty}^{+\infty} \hspace{0.2cm} \int_{- 1/(2T)}^{1/(2T)}G_{\rm Nyq}(f\hspace{0.08cm}' - \frac{k}{T} ) \cdot {\rm e}^{ {\rm j} \hspace{0.05cm}2 \pi \hspace{0.02cm}f\hspace{0.08cm}' \hspace{0.02cm} \nu \hspace{0.05cm}T}\,{\rm d} f \hspace{0.08cm}' = 0 \hspace{0.05cm}.$$

(6)   Swapping summation and integration and renaming  $f\hspace{0.08cm}'$  to  $f$,  it further follows:

$$\int_{-1/(2T)}^{1/(2T)}\hspace{0.2cm} \sum_{k = - \infty}^{+\infty} G_{\rm Nyq}(f - \frac{k}{T} ) \cdot {\rm e}^{ {\rm j} \hspace{0.05cm}2 \pi \hspace{0.02cm}f \hspace{0.02cm} \nu \hspace{0.05cm}T}\,{\rm d} f = 0 \hspace{0.05cm}.$$

(7)   This requirement can be satisfied for all  $\nu \ne 0$  only if the infinite sum is independent of  $f$,  i.e.,  has a constant value:

$$\sum_{k = -\infty}^{+\infty} G_{\rm Nyq}(f - \frac{k}{T} ) = K_{\rm Nyq} \hspace{0.05cm}.$$

(8)   From the penultimate equation,  we obtain simultaneously for  $\nu = 0$:

$$\int_{-1/(2T)}^{1/(2T)}\hspace{0.2cm} \sum_{k = -\infty}^{+\infty} G_{\rm Nyq}(f - \frac{k}{T} ) \,{\rm d} f = K_{\rm Nyq} \cdot \frac{1}{T} = g_0 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}K_{\rm Nyq} = g_0 \cdot T \hspace{0.05cm}.$$
q.e.d.


1/T Nyquist spectra


Nyquist spectra which are limited to the frequency range  $-1/T \le f \le +1/T$  and are coherent,  have a particular importance for digital signal transmission.

The diagram shows the  "trapezoidal characteristic"  and the  "cosine rolloff characteristic",  which are two variants in this respect. The same applies to both Nyquist spectra:

  • The rolloff occurs between the two corner frequencies  $f_1$  and  $f_2$  point-symmetrically about the  Nyquist frequency  $f_{\rm Nyq} = (f_1+f_2)/2$. 
    That is,  for  $0 \le f \le f_{\rm Nyq}$: 
$$G_{\rm Nyq}(f_{\rm Nyq}+f) + G_{\rm Nyq}(f_{\rm Nyq}-f) = g_0 \cdot T \hspace{0.05cm}.$$
  • For all frequencies  $|f| \le f_1$,  the function  $G_{\rm Nyq}(f)$  is constantly equal to  $g_0 \cdot T$  and for  $|f| \ge f_2$  it is identically zero.
$1/T$  Nyquist spectra
  • In the range between  $f_1$  and  $f_2$  holds:
$$\frac{G_{\rm Nyq}(f)}{g_0 \cdot T } = \left\{ \begin{array}{c} \frac{f_2 - |f|}{f_2 -f_1 } \\ \\ \cos^2( \frac{\pi}{2}\cdot \frac{f_2 - |f|}{f_2 -f_1 }) \\ \end{array} \right.\quad \begin{array}{*{1}c} {\rm{at \hspace{0.15cm}trapezoidal}\hspace{0.05cm},} \\ \\ {\rm{\rm{at \hspace{0.15cm}cosine \hspace{0.15cm}rolloff}}\hspace{0.05cm}.} \\ \end{array}$$
  • To parameterize the slope,  we use the  rolloff factor  $r$,  which can take values between  $0$  and  $1$  (including these limits):
$$r = \frac{f_2 -f_1 } {f_2 +f_1 } \hspace{0.05cm}.$$
In the literature,  the rolloff factor is sometimes referred to as  $\alpha$  ("alpha").
  • For  $r = 0$   ⇒   $f_1 = f_2 = f_{\rm Nyq}$  we obtain in both cases the  (green–dotted)  rectangular Nyquist spectrum.
  • The rolloff factor  $r = 1$   ⇒   $f_1 = 0, \ f_2 = 2 f_{\rm Nyq}$  stands
  1. for the triangular spectrum
  2. resp.  the cosine-square spectrum, 
depending on which of the two basic structures shown above one assumes.  These frequency curves are shown in red dashed lines.



Time domain description of the 1/T Nyquist spectra


Let us now consider the Nyquist pulses.  For the  trapezoidal spectrum  with rolloff factor  $r$,  we obtain:

$$g_{_{\rm trapezoid}} ( t )= g_0 \cdot {\rm sinc} \left ( \frac{t}{T}\right)\cdot {\rm sinc} \left ( \frac{r \cdot t}{T}\right) \hspace{0.5cm}{\rm with }\hspace{0.5cm}{\rm sinc}(x) = {\rm sin}(\pi x)/(\pi x) .$$

In contrast,  the Fourier inverse transform of the  cosine rolloff spectrum  (short:  "CRO spectrum") yields:

$$g_{_{\rm CRO}} ( t )= g_0 \cdot {\rm sinc} \left ( \frac{ t}{T}\right)\cdot \frac{\cos(\pi \cdot r \cdot t/T)}{1 - (2 \cdot r \cdot t/T)^2 } \hspace{0.3cm}{\rm with }\hspace{0.3cm}{\rm sinc}(x) = {\rm sin}(\pi x)/(\pi x).$$

These pulses can be viewed using the HTML5/JS applet  "Frequency & Impulse Responses"  $($with setting  $ \Delta \cdot f = 1)$,  illustrating the influence of the rolloff factor  $r$. 

The following upper diagram shows the Nyquist pulse with trapezoidal spectrum for different rolloff factors. Below is the corresponding time course for the cosine rolloff spectrum. One can see:

Nyquist pulses with trapezoidal and cosine rolloff spectrum
  1. The smaller the rolloff factor  $r$,  the slower the decay of the Nyquist pulse. This statement is true for both the trapezoidal and the cosine rolloff spectra.
  2. In the limiting case  $r \to 0$,  both cases yield the rectangular Nyquist spectrum and the  $\rm sinc$–shaped Nyquist pulse,   which decays asymptotically with  $1/t$  (thin green curves).
  3. For an average rolloff  $(r \approx 0.5)$,  the first overshoots are smaller for the trapezoidal spectrum than for the CRO spectrum,  because here the Nyquist slope is flatter for a given  $r$  (blue curves).
  4. With the rolloff factor  $r = 1$,  the trapezoid becomes a triangle in the frequency domain and the CRO spectrum becomes the  "cosine–square spectrum".  In the diagrams in the  "last section"  these spectral functions are drawn in red.
  5. With  $r = 1$  the asymptotically decay of the upper time function  (according to the trapezoidal spectrum)  occurs with  $1/t^2$,  the decay of the lower function  (according to the CRO spectrum)  with  $1/t^3$.
  6. This means:   After a longer time,  the CRO Nyquist pulse has settled better than the trapezoidal Nyquist pulse.


Second Nyquist criterion


Before the exact mathematical definition,  the significance of the  second Nyquist criterion  for the evaluation of a digital system is illustrated by means of diagrams. The graphic shows three examples of Nyquist systems,  in each case:

  • at the top,  the Nyquist spectrum  $G_d(f)$,
  • below the corresponding  "eye diagram"  referring to the  "third main chapter".
Clarification of first and second Nyquist criterion


$\text{Interpretation:}$

  • The diagram on the left shows the eye diagram of a Nyquist system with cosine rolloff characteristic,  where the rolloff factor  $r= 0.5$  was chosen.  Since the first Nyquist criterion is fulfilled here  (there is point symmetry around the Nyquist frequency  $f_{\rm Nyq}$,  the vertical eye opening at time  $t = 0$  is  $2 \cdot g_d(0)$.  All eye lines pass at time  $t = 0$  through one of the two points marked in red   ⇒   the eye is vertically maximally open.


  • The middle spectrum does not show any symmetry with respect to the rolloff,  so that the first Nyquist criterion is not fulfilled here – in contrast to the second one.  All eyelines here intersect the time axis at the same times  (marked by the green dots),  which facilitates,  for example,  clock recovery by means of a  $\rm PLL$  ("Phase-Locked Loop").  When the second Nyquist criterion is met,  the horizontal eye opening is maximally equal to the symbol duration $T$   ⇒   the eye is maximally open horizontally.


  • The right eye diagram illustrates that for the CRO spectrum with  $r = 1$,  both the first and second Nyquist criteria are satisfied.  Here,  the Nyquist pulse
$$g_d ( t )= g_0 \cdot \frac{\pi }{4}\cdot {\rm sinc} \left ( \frac{ t}{T}\right)\cdot \left [ {\rm sinc} (\frac{t}{T} + \frac{1}{2}) + {\rm sinc} (\frac{t}{T} - \frac{1}{2})\right]$$
exhibits the required zero crossings at  $t = \pm T$,  $t = \pm 1.5T$,  $t = \pm 2T$,  $t = \pm 2.5T$, ... but not at  $t = \pm 0.5T$. The pulse amplitude is  $g_d(t = 0) = g_0$.    
Note:   No other pulse satisfies both the first and second Nyquist criteria simultaneously.


$\text{Summary of Nyquist criteria:}$

(1)   In memory of the physicist  "Harry Nyquist"  we denote a basic detection pulse  $g_d( t)$  with the properties

$$g_d ( t= 0) \ne 0, \hspace{1cm} g_d ( t)= 0 \hspace{0.3cm}{\rm{for} }\hspace{0.3cm} t = \pm T, \pm 2T,\pm 3T,\hspace{0.05cm}\text{...}$$
as the  Nyquist–1 pulse  $g_{\hspace{0.05cm}\rm Nyq-1}(t)$.  This satisfies the first Nyquist criterion and leads to the maximum vertical eye opening.

(2)   A basic detection pulse  $g_d( t)$  satisfying the second Nyquist criterion must have zero crossings at  $t = \pm 1.5T$,  $t = \pm 2.5T$, ...  have:

$$g_d ( t= 0.5) \ne 0, \hspace{0.8cm} g_d ( t)= 0 \hspace{0.3cm}{\rm{for} }\hspace{0.3cm} t = \pm 1.5T, \ \pm 2.5T,\ \pm 3.5T,\hspace{0.05cm}\text{...}$$
Such a  Nyquist–2 pulse  leads to the maximum horizontal eye opening.

(3)   A Nyquist–2 pulse can always be represented as the sum of two Nyquist–1 pulses shifted by  $t = \pm T/2$: 

$$g_{\rm Nyq-2} ( t )= g_{\rm Nyq-1} ( t +T/2)+g_{\rm Nyq-1} ( t -T/2)\hspace{0.05cm}.$$

(4)   In the frequency domain,  the second Nyquist criterion  (see [TS87] [1]) is:

$$\sum_{k = -\infty}^{+\infty} \frac {G_d \left ( f -k/T \right)}{\cos(\pi \cdot f \cdot T - k \cdot \pi)}= {\rm const.}$$


$\text{Example 3:}$  Starting from the Nyquist–1 pulse  $g_{\rm Nyq-1}( t )= g_0 \cdot {\rm sinc}(t/T)$  the corresponding Nyquist–2 pulse is:

$$g_{\rm Nyq-2}( t ) = g_0 \cdot \left [ {\rm sinc}( \frac{t + T/2}{T}) + {\rm sinc}( \frac{t- T/2}{T}) \right] =\frac{2 \cdot g_0}{\pi} \cdot \frac{\cos(\pi \cdot t/T)}{1 - (2 \cdot t/T)^2}\hspace{0.05cm}.$$
  • Due to the limitation of the spectrum  $G_{\rm Nyq-1}( f)$  to the range  $\vert f \vert \le f_{\rm Nyq} = 1/(2T)$,  the sum in equation  (4)  is limited to the term with  $k = 0$,  and we obtain:
$$G_{\rm Nyq-2}(f) = \left\{ \begin{array}{c} g_0 \cdot T \cdot \cos(\pi/2 \cdot f/f_{\rm Nyq}) \\ \\ 0 \\\end{array} \right.\quad \begin{array}{*{1}c} {\rm{for} }\hspace{0.15cm} \vert f \vert < f_{\rm Nyq}\hspace{0.05cm}, \\ \\ {\rm{otherwise} }\hspace{0.05cm}. \\ \end{array}$$
  • This frequency response and the corresponding eye diagram is sketched in the middle column of the above diagram.
  • From the bottom diagram, one can clearly see the fulfillment of the second Nyquist criterion.


Exercises for the chapter


Exercise 1.4: Nyquist Criteria

Exercise 1.4Z: Complex Nyquist Spectrum

Exercise 1.5: Cosine-Square Spectrum

References

  1. Tröndle, K.; Söder, G.:  Optimization of Digital Transmission Systems.  Boston – London:  Artech House, 1987.