Difference between revisions of "Digital Signal Transmission/Linear Nyquist Equalization"

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{{Header
 
{{Header
|Untermenü=Impulsinterferenzen und Entzerrungsverfahren
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|Untermenü=Intersymbol Interfering and Equalization Methods
 
|Vorherige Seite=Impulsinterferenzen bei mehrstufiger Übertragung
 
|Vorherige Seite=Impulsinterferenzen bei mehrstufiger Übertragung
 
|Nächste Seite=Entscheidungsrückkopplung
 
|Nächste Seite=Entscheidungsrückkopplung
 
}}
 
}}
  
== Struktur des optimalen Nyquistentzerrers ==
+
== Structure of the optimal Nyquist equalizer ==
 
<br>
 
<br>
In diesem Abschnitt gehen wir von folgendem Blockschaltbild eines Binärsystems aus.<br>
+
In this section we assume the following block diagram of a binary system.&nbsp; In this regard,&nbsp; it should be noted:
 +
[[File:EN_Dig_T_3_5_S1.png|right|frame|Block diagram of the optimal Nyquist equalizer|class=fit]]
  
[[File:P ID1423 Dig T 3 5 S1 version1.png|Blockschaltbild des optimalen Nyquistentzerrers|class=fit]]<br>
+
*The&nbsp; "Dirac source"&nbsp; provides the message to be transmitted in binary bipolar form  &nbsp; &rArr; &nbsp; amplitude coefficients &nbsp;$a_\nu \in \{ -1, \hspace{0.05cm}+1\}$.&nbsp; The source is assumed to be redundancy-free.
  
Hierzu ist anzumerken:
+
*The&nbsp; "transmission pulse shape" &nbsp;$g_s(t)$&nbsp; is taken into account by the transmitter frequency response &nbsp;$H_{\rm S}(f)$.&nbsp; Mostly, &nbsp;$H_{\rm S}(f) = {\rm sinc}(f T)$&nbsp; is based &nbsp; &rArr; &nbsp; NRZ rectangular transmission pulses.
*Die Diracquelle liefert die zu übertragende Nachricht (Amplitudenkoeffizienten <i>a<sub>&nu;</sub></i>) in binärer bipolarer Form. Sie wird als redundanzfrei vorausgesetzt.<br>
 
  
*Die Sendeimpulsform <i>g<sub>s</sub></i>(<i>t</i>) wird durch den Senderfrequenzgang <i>H</i><sub>S</sub>(<i>f</i>) berücksichtigt. Bei allen Beispielen ist <i>H</i><sub>S</sub>(<i>f</i>) = si(&pi; <i>f</i> <i>T</i>) zugrunde gelegt.<br>
+
*In some derivations,&nbsp; transmitter and channel are combined by the&nbsp; "common frequency response" &nbsp;$H_{\rm SK}(f) = H_{\rm S}(f) \cdot H_{\rm K}(f)$.&nbsp; <br>
  
*Bei manchen Herleitungen werden Sender und Kanal &ndash; hierfür wird meist ein Koaxialkabel angenommen &ndash; durch den gemeinsamen Frequenzgang <i>H</i><sub>SK</sub>(<i>f</i>) = <i>H</i><sub>S</sub>(<i>f</i>) &middot; <i>H</i><sub>K</sub>(<i>f</i>) zusammengefasst.<br>
+
*The receiver filter &nbsp;$H_{\rm E}(f)$&nbsp; is multiplicatively composed of the &nbsp;[[Theory_of_Stochastic_Signals/Matched_Filter|matched filter]]&nbsp; $H_{\rm MF}(f) = H_{\rm SK}^\star(f)$&nbsp; and the &nbsp;[[Digital_Signal_Transmission/Linear_Nyquist_Equalization#Operating_principle_of_the_transversal_filter|transversal filter]]&nbsp; $H_{\rm TF}(f)$,&nbsp; at least it can be split up mentally in this way.
  
*Das Empfangsfilter <i>H</i><sub>E</sub>(<i>f</i>) setzt sich multiplikativ aus dem Matched&ndash;Filter <i>H</i><sub>MF</sub>(<i>f</i>) = <i>H</i><sub>SK</sub><sup>&#8727;</sup>(<i>f</i>) und dem Transversalfilter <i>H</i><sub>TF</sub>(<i>f</i>) zusammen, zumindest kann es gedanklich so aufgespalten werden.
+
*The overall frequency response between Dirac source and threshold decision should satisfy the &nbsp;[[Digital_Signal_Transmission/Properties_of_Nyquist_Systems#First_Nyquist_criterion_in_the_frequency_domain| "first Nyquist condition"]].&nbsp; Thus, it must hold:
 
+
:$$H_{\rm S}(f) \cdot H_{\rm K}(f) \cdot H_{\rm MF}(f) \cdot H_{\rm TF}(f)
*Der Gesamtfrequenzgang zwischen der Diracquelle und dem Schwellenwertentscheider soll die [http://en.lntwww.de/Digitalsignal%C3%BCbertragung/Eigenschaften_von_Nyquistsystemen#Erstes_Nyquistkriterium_im_Frequenzbereich erste Nyquistbedingung] erfüllen. Es muss also gelten:
 
 
 
::<math>H_{\rm S}(f) \cdot H_{\rm K}(f) \cdot H_{\rm MF}(f) \cdot H_{\rm TF}(f)
 
 
  = H_{\rm Nyq}(f)
 
  = H_{\rm Nyq}(f)
  \hspace{0.05cm}.</math>
+
  \hspace{0.05cm}.$$
  
*Mit dieser Bedingung ergibt sich die maximale Augenöffnung (keine Impulsinterferenzen). Deshalb gelten für das Detektions&ndash;SNR und den Systemwirkungsgrad bei binärer Signalisierung:
+
*With this condition, there is no&nbsp;                                          [[Digital_Signal_Transmission/Causes_and_Effects_of_Intersymbol_Interference|"intersymbol interference"]]&nbsp; $\rm (ISI)$ and the maximum eye opening is obtained.&nbsp;  
  
::<math>\rho_d = \frac{2 \cdot s_0^2 \cdot T}{\sigma_d^2} =  \frac{2 \cdot s_0^2 \cdot T}{N_0}\cdot \frac{1}{\sigma_{d,\hspace{0.05cm} {\rm norm}}^2}
+
*Therefore, the &nbsp;[[Digital_Signal_Transmission/Error_Probability_for_Baseband_Transmission#Optimal_binary_receiver_.E2.80.93_.22Matched_Filter.22_realization|"detection SNR"]]&nbsp; and &nbsp;[[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_peak_limitation|"system efficiency"]]&nbsp; for binary signaling are:
 +
:$$\rho_d = \frac{2 \cdot s_0^2 \cdot T}{\sigma_d^2} =  \frac{2 \cdot s_0^2 \cdot T}{N_0}\cdot \frac{1}{\sigma_{d,\hspace{0.05cm} {\rm norm}}^2}
 
   \hspace{0.3cm}\Rightarrow \hspace{0.3cm}
 
   \hspace{0.3cm}\Rightarrow \hspace{0.3cm}
 
  \eta = \frac{\rho_d }{\rho_{d,\hspace{0.05cm} {\rm max}}}
 
  \eta = \frac{\rho_d }{\rho_{d,\hspace{0.05cm} {\rm max}}}
 
= \frac{\rho_d }{2 \cdot s_0^2 \cdot T/N_0}
 
= \frac{\rho_d }{2 \cdot s_0^2 \cdot T/N_0}
 
= \frac{1}{\sigma_{d,\hspace{0.05cm} {\rm norm}}^2}
 
= \frac{1}{\sigma_{d,\hspace{0.05cm} {\rm norm}}^2}
\hspace{0.05cm}.</math>
+
\hspace{0.05cm}.$$
  
*Die Optimierungsaufgabe beschränkt sich also darauf, das Empfangsfilter <i>H</i><sub>E</sub>(<i>f</i>) so zu bestimmen, dass die normierte Rauschleistung vor dem Entscheider den kleinstmöglichen Wert annimmt:
+
*The optimization task is therefore limited to determining the receiver filter &nbsp;$H_{\rm E}(f)$&nbsp; such <br>'''that the normalized noise power before the decision takes the smallest possible value''':
  
 
::<math>\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = \frac{\sigma_d^2}{N_0/
 
::<math>\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = \frac{\sigma_d^2}{N_0/
 
T} =T \cdot \int_{-\infty}^{+\infty} |H_{\rm E}(f)|^2
 
T} =T \cdot \int_{-\infty}^{+\infty} |H_{\rm E}(f)|^2
\,{\rm d} f \stackrel {!}{=} {\rm Minimum}\hspace{0.05cm}.</math>
+
\,{\rm d} f \stackrel {!}{=} {\rm minimum}\hspace{0.05cm}.</math>
  
*Wir bezeichnen die Konfiguration als Optimale Nyquistentzerrung (ONE). Obwohl diese auch &ndash; und besonders effektiv &ndash; bei Mehrstufensystemen anwendbar ist, setzen wir zunächst <i>M</i> = 2.<br><br>
+
{{BlaueBox|TEXT= 
 +
$\text{Definition:}$&nbsp; We refer to the configuration described here as &nbsp;'''Optimal Nyquist Equalization'''&nbsp; $\rm (ONE)$.}}
  
== Wirkungsweise des Transversalfilters (1) ==
 
<br>
 
Verdeutlichen wir uns zunächst die Aufgabe des symmetrischen Transversalfilters
 
  
:<math>H_{\rm TF}(f) \hspace{0.4cm}\bullet\!\!-\!\!\!-\!\!\!-\!\!\circ
+
Although this can also &ndash; and especially effectively &ndash; be applied to multi-level systems, we initially set &nbsp;$M = 2$.
 +
 
 +
== Operating principle of the transversal filter==
 +
 
 +
[[File:P ID1424 Dig T 3 5 S2 version2.png|right|frame|Second order transversal filter  as part of the optimal Nyquist equalizer|class=fit]]
 +
<br>Let us first clarify the task of the symmetric transversal filter with frequency response
 +
:$$H_{\rm TF}(f) \hspace{0.4cm}\bullet\!\!-\!\!\!-\!\!\!-\!\!\circ
 
  \hspace{0.4cm}  
 
  \hspace{0.4cm}  
 
h_{\rm TF}(t) = \sum_{\lambda = -N}^{+N} k_\lambda \cdot \delta(t - \lambda \cdot T)
 
h_{\rm TF}(t) = \sum_{\lambda = -N}^{+N} k_\lambda \cdot \delta(t - \lambda \cdot T)
  \hspace{0.05cm}.</math>
+
$$
  
<i>N</i> gibt die Ordnung des Filters an. Für die Filterkoeffizienten gilt <i>k</i><sub>&ndash;&lambda;</sub> = <i>k</i><sub>&lambda;</sub>. Dieses Filter ist somit durch die Koeffizienten <i>k</i><sub>0</sub>, ... , <i>k<sub>N</sub></i> vollständig bestimmt. Die Grafik zeigt ein Filter zweiter Ordnung (<i>N</i> = 2).<br>
+
and the following properties:
 +
*$N$&nbsp; indicates the&nbsp; "order"&nbsp; of the filter &nbsp; &rArr; &nbsp; the graph shows a second order filter &nbsp;$(N=2)$.
 +
 +
*For the filter coefficients &nbsp;$k_{-\lambda} = k_{\lambda}$ &nbsp; &rArr; &nbsp; symmetric structure &nbsp; &rArr; &nbsp; $H_{\rm TF}(f)$ is real.
  
[[File:P ID1424 Dig T 3 5 S2 version2.png|Transversalfilter als Teil des optimalen Nyquistentzerrers|class=fit]]<br>
+
*$H_{\rm TF}(f)$&nbsp; is thus completely determined by the coefficients &nbsp;$k_0$, ... , $k_N$.
  
Für den Eingangsimpuls <i>g<sub>m</sub></i>(<i>t</i>) setzen wir ohne Einschränkung der Allgemeingültigkeit voraus, dass dieser
 
  
*symmetrisch um <i>t</i> = 0 ist (Ausgang des Matched&ndash;Filters),<br>
+
For the input pulse &nbsp;$g_m(t)$&nbsp; we assume without restriction of generality that it
*zu den Zeiten <i>&nu;</i><i>T</i> und &ndash;<i>&nu;</i><i>T</i> den Wert <i>g<sub>m</sub></i>(<i>&nu;</i>) besitzt.<br><br>
 
  
Damit sind die Eingangsimpulswerte:
+
*is symmetric about &nbsp;$t=0$&nbsp; (output of the matched filter),<br>
 +
*has the value &nbsp;$g_m(\nu)$&nbsp; at times &nbsp;$\nu \cdot T$&nbsp; and &nbsp;$-\nu \cdot T$,&nbsp; respectively.<br>
  
:<math>...\hspace{0.2cm} , g_m(3),\hspace{0.15cm}g_m(2),\hspace{0.15cm}g_m(1),\hspace{0.15cm}\hspace
+
 
 +
Thus,&nbsp; the input pulse values are:
 +
:$$\text{...}\hspace{0.2cm} , g_m(3),\hspace{0.15cm}g_m(2),\hspace{0.15cm}g_m(1),\hspace{0.15cm}\hspace
 
{0.15cm}g_m(0),\hspace{0.15cm}g_m(1),\hspace{0.15cm}g_m(2),\hspace{0.15cm}g_m(3),\hspace{0.1cm}
 
{0.15cm}g_m(0),\hspace{0.15cm}g_m(1),\hspace{0.15cm}g_m(2),\hspace{0.15cm}g_m(3),\hspace{0.1cm}
... \hspace{0.05cm}.</math>
+
\text{...}\hspace{0.05cm}.$$
  
Für den Detektionsgrundimpuls <i>g<sub>d</sub></i>(<i>t</i>) am Filterausgang ergeben sich demzufolge zu den Zeitpunkten <i>&nu;</i><i>T</i> mit den Abkürzungen <i>g</i><sub>0</sub> = <i>g<sub>d</sub></i>(<i>t</i> = 0), <i>g</i><sub>1</sub> = <i>g<sub>d</sub></i>(<i>t</i> = &plusmn;<i>T</i>), <i>g</i><sub>2</sub> = <i>g<sub>d</sub></i>(<i>t</i> = &plusmn;2<i>T</i>) folgende Werte:
+
Consequently,&nbsp; for the basic detection pulse &nbsp;$g_d(t)$&nbsp; at the filter output, the following values result at the time instants &nbsp;$\nu \cdot T$&nbsp; with the abbreviations &nbsp;$g_0 =g_d(t= 0)$, &nbsp; $g_1 =g_d(t= \pm T)$, &nbsp; $g_2 =g_d(t= \pm 2T)$:&nbsp;  
 +
:$$ t = 0\hspace{-0.1cm}:\hspace{0.9cm}g_0  =  k_0 \cdot g_m(0) + k_1 \cdot 2
 +
\cdot g_m(1) \hspace{1.23cm}+k_2 \cdot 2 \cdot g_m(2),\hspace{0.05cm} $$
 +
:$$ t = \pm T\hspace{-0.1cm}:\hspace{0.45cm}g_1  =  k_0 \cdot g_m(1) + k_1
 +
\cdot \big [g_m(0)+g_m(2)]+ k_2 \cdot [g_m(1)+g_m(3) \big ], $$
 +
:$$ t = \pm 2T\hspace{-0.1cm}:\hspace{0.2cm}g_2  =  k_0 \cdot g_m(2) + k_1
 +
\cdot \big [g_m(1)+g_m(3)\big ]+ k_2  \cdot \big [g_m(2)+g_m(4)\big ]
 +
\hspace{0.05cm}. $$
  
:<math> t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0  = k_0 \cdot g_m(0) + k_1 \cdot 2
+
From this system with three linearly independent equations,&nbsp; one can determine the filter coefficients &nbsp;$k_0$, &nbsp;$k_1$&nbsp; and&nbsp; $k_2$&nbsp; in such a way that the basic detection pulse &nbsp;$g_d(t)$&nbsp; has the following interpolation points:
\cdot g_m(1) \hspace{1.23cm}+k_2 \cdot 2 \cdot g_m(2),\hspace{0.05cm} </math>
+
:$$\text{...}\hspace{0.15cm} , g_3,\hspace{0.25cm}g_2 = 0 ,\hspace{0.15cm}g_1 = 0
:<math> t = \pm T\hspace{-0.1cm}:\hspace{0.2cm}g_1  = k_0 \cdot g_m(1) + k_1
+
,\hspace{0.15cm}g_0 = 1,\hspace{0.15cm}g_1 = 0 ,\hspace{0.15cm}g_2
\cdot [g_m(0)+g_m(2)]+ k_2 \cdot [g_m(1)+g_m(3)], </math>
+
= 0 ,\hspace{0.25cm}g_3 ,\hspace{0.15cm} \text{...}$$
:<math> t = \pm 2T\hspace{-0.1cm}:\hspace{0.2cm}g_2  =  k_0 \cdot g_m(2) + k_1
 
\cdot [g_m(1)+g_m(3)]+ k_2  \cdot [g_m(2)+g_m(4)]
 
\hspace{0.05cm}. </math>
 
  
Aus diesem System mit drei linear unabhängigen Gleichungen kann man nun die Filterkoeffizienten <i>k</i><sub>0</sub>, <i>k</i><sub>1</sub> und <i>k</i><sub>2</sub> so bestimmen, dass der Detektionsgrundimpuls <i>g<sub>d</sub></i>(<i>t</i>) durch die normierten Stützstellen
+
{{GraueBox|TEXT= 
 +
$\text{Example 1:}$&nbsp; We assume the symmetrical input signal according to the upper diagram in the graph. With the abbreviation &nbsp;$g_m(\nu)= g_m(\pm \nu \cdot T)$&nbsp; there are the following samples at the distance of the symbol duration &nbsp;$T$:
 +
:$$g_m(t) = {\rm e}^{  - \sqrt{2 \hspace{0.05cm} \cdot \hspace{0.05cm}\vert\hspace{0.05cm} t \hspace{0.05cm} \vert /T} }\hspace{0.3cm}
 +
\Rightarrow \hspace{0.3cm} g_m(0) = 1 ,\hspace{0.35cm}g_m(1)=
 +
0.243,\hspace{0.35cm}g_m(2)= 0.135,\hspace{0.35cm}g_m(3)= 0.086,
 +
\hspace{0.35cm}g_m(4)= 0.059 \hspace{0.05cm}.$$
  
:<math>...\hspace{0.15cm} , g_3,\hspace{0.25cm}g_2 = 0 ,\hspace{0.15cm}g_1 = 0
+
&rArr; &nbsp; For the output pulse &nbsp;$g_d(t =0) = 1$&nbsp; and&nbsp;  $g_d(t =\pm T) = 0$&nbsp; should be valid.&nbsp; For this purpose,&nbsp; a first-order delay filter with coefficients &nbsp;$k_0$&nbsp; and&nbsp;  $k_1$ is suitable,&nbsp; which must satisfy the following conditions:
,\hspace{0.15cm}g_0 = 1,\hspace{0.15cm}g_1 = 0 ,\hspace{0.15cm}g_2
+
[[File:P ID1425 Dig T 3 5 S2b version1.png|right|frame|Input and output pulse of the <br>optimal Nyquist equalizer]]
= 0 ,\hspace{0.25cm}g_3 ,\hspace{0.15cm} ...</math>
+
:$$t = \pm T\hspace{-0.1cm}  :  \hspace{0.2cm}g_1 = k_0 \cdot 0.243 + k_1 \cdot
 +
\big [1.000 +0.135 \big  ] = 0\hspace{0.3cm}\Rightarrow
 +
\hspace{0.3cm}{k_1} =
 +
-0.214 \cdot {k_0}\hspace{0.05cm},$$
 +
:$$ t = 0 \hspace{-0.1cm}  :  \hspace{0.6cm}g_0 = k_0 \cdot 1.000 + k_1 \cdot 2 \cdot
 +
0.243= 1\hspace{0.3cm}\Rightarrow \hspace{0.3cm}0.896 \cdot {k_0}
 +
= 1 \hspace{0.05cm}.$$
 +
 
 +
From this,&nbsp; the optimal filter coefficients &nbsp;$k_0 = 1.116$&nbsp; and&nbsp; $k_1 = 0.239$ are obtained.
 +
*The middle diagram shows that thus the first precursor and the first trailer can be compensated and at the same time &nbsp;$g_d(0) =1$&nbsp; is valid&nbsp; (yellow background).
 +
 
 +
*However,&nbsp; the further basic detection pulse values (blue circles) are different from zero and cause intersymbol interference.<br><br>
 +
 
 +
&rArr; &nbsp; The lower diagram shows that with a second order filter &nbsp;$(N = 2)$&nbsp; zero crossings are forced at &nbsp;$\pm T$&nbsp; and at &nbsp;$\pm 2T$&nbsp; if the coefficients &nbsp;$k_0 = 1.127$, &nbsp;$k_1 = 0.219$&nbsp; and&nbsp; $k_2 =  0.075$&nbsp; are suitably chosen. The system of equations for determining the optimal coefficients is thereby:
 +
:$$t = 0\hspace{-0.1cm}:\hspace{0.85cm}g_0 =  k_0 \cdot 1.000 + k_1 \cdot 2
 +
\cdot  0.243 + k_2 \cdot 2 \cdot 0.135 = 1\hspace{0.05cm},$$
 +
:$$t= \pm T\hspace{-0.1cm}:\hspace{0.45cm}g_1 = k_0 \cdot 0.243 + k_1 \cdot
 +
\big [1.000+0.135 \big ]+ k_2  \cdot \big [0.243+0.086 \big ] = 0\hspace{0.05cm},$$
 +
:$$t = \pm 2 T\hspace{-0.1cm}:\hspace{0.2cm}g_2 =  k_0 \cdot 0.135 + k_1 \cdot
 +
\big [0.243+0.086\big ]+ k_2 \cdot \big [1.000 + 0.059 \big ]= 0 \hspace{0.05cm}.$$}}<br>
 +
 
 +
{{BlaueBox|TEXT= 
 +
$\text{Conclusion:}$&nbsp; The results can be generalized as follows:
 +
#With an &nbsp;$N$&ndash;th order delay filter,&nbsp; the main value  can be made to &nbsp;$g_d(0)=1$&nbsp; (normalized).
 +
#The first $N$&nbsp; trailers &nbsp;$g_{\nu}$&nbsp; and the first $N$&nbsp;  precursors &nbsp;$g_{-\nu}$&nbsp; can be made to zero.<br>
 +
#Further precursors and trailers &nbsp;$(\nu \gt N)$&nbsp; cannot be compensated in this way.&nbsp; 
 +
#It is even possible that the precursors and trailers outside the compensation range are enlarged or even new ones are created.<br>
 +
#In the limit &nbsp;$N \to \infty$&nbsp; (in practice this means: &nbsp; a filter with very many coefficients)&nbsp;  a complete Nyquist equalization and thus an ISI-free transmission is possible.}}
  
vollständig gegeben ist. Auf der nächsten Seite wird die Optimierung der Filterkoeffizienten an einem einfachen Beispiel verdeutlicht.<br>
 
  
== Wirkungsweise des Transversalfilters (2) ==
+
== Description in the frequency domain ==
 
<br>
 
<br>
{{Beispiel}}''':''' Wir gehen von dem symmetrischen Eingangssignal entsprechend dem oberen Diagramm aus. Mit der Abkürzung <i>g<sub>m</sub></i>(<i>&nu;</i>) = <i>g<sub>m</sub></i>(&plusmn; <i>&nu;</i> &middot; <i>T</i>) gibt es folgende Abtastwerte im Abstand der Symboldauer <i>T</i>:
+
The fact that the optimal Nyquist equalizer is multiplicatively derived from
 +
*the matched filter &nbsp;$H_{\rm MF}(f) = H_{\rm S}^\star (f)\cdot H_{\rm K}^\star(f)$&nbsp; &ndash; i.e. matched to the basic receiver pulse &nbsp;$g_r(t)$&nbsp; &ndash; and<br>
 +
*a transversal filter &nbsp;$H_{\rm MF}(f)$&nbsp; with infinitely many filter coefficients<br><br>
  
:<math>g_m(t) = {\rm exp }\left ( - \sqrt{2 \cdot |t|/T}\right )</math>
+
follows from the first Nyquist criterion.&nbsp; By applying the &nbsp;[https://en.wikipedia.org/wiki/Calculus_of_variations&nbsp; "Calculus of Variations"],&nbsp; the frequency response of the transversal filter is obtained &nbsp; &ndash; see [TS87]<ref name='TS87'>Tröndle, K.; Söder, G.:&nbsp; Optimization of Digital Transmission Systems.&nbsp; Boston – London: Artech House, 1987,&nbsp; ISBN:&nbsp; 0-89006-225-0.</ref>:
 +
[[File:Dig_T_3_5_S3b_version2.png|right|frame|Magnitude frequency response of the transversal filter&nbsp; (left) and the entire optimal Nyquist equalizer&nbsp; (right)|class=fit]]
 +
$$H_{\rm TF}(f) = \frac{1}{\sum\limits_{\kappa = -\infty}^{+\infty}  |H_{\rm SK}(f -
 +
\frac{\kappa}{T})
 +
|^2},$$
 +
$$\text{where }H_{\rm SK}(f) = H_{\rm S}(f)\cdot H_{\rm K}(f).$$
  
:<math>\Rightarrow \hspace{0.3cm} g_m(0) = 1 ,\hspace{0.15cm}g_m(1)=
+
The left graph shows &nbsp;$20 \cdot \lg \ H_{\rm TF}(f)$&nbsp; in the range &nbsp;$| f | \le 1/T$. This assumes rectangular NRZ transmission pulses and a coaxial cable with the characteristic cable attenuation &nbsp;$a_\star$.  
0.243,\hspace{0.15cm}g_m(2)= 0.135,\hspace{0.15cm}g_m(3)= 0.086,
 
\hspace{0.15cm}g_m(4)= 0.059 \hspace{0.05cm}.</math>
 
  
Für den Ausgangsimpuls soll <i>g<sub>d</sub></i>(0) = 1 und <i>g<sub>d</sub></i>(&plusmn;<i>T</i>) = 0 gelten. Hierzu eignet sich ein Laufzeitfilter erster Ordnung mit den Koeffizienten <i>k</i><sub>0</sub> und <i>k</i><sub>1</sub>, die folgende Bedingungen erfüllen müssen:
+
One can see from the equation and the left graph:
 +
*$H_{\rm TF}(f)$&nbsp; is&nbsp; "real",&nbsp; which results in the symmetrical structure of the transversal filter: &nbsp; $k_{-\lambda} =k_{+\lambda} $.<br>
  
:<math>t = \pm T\hspace{-0.1cm:  \hspace{0.2cm}g_1 = k_0 \cdot 0.243 + k_1 \cdot
+
*$H_{\rm TF}(f)$&nbsp; is at the same time &nbsp; "periodic"&nbsp; with frequency &nbsp;$1/T$.
[1.000 +0.135] = 0\hspace{0.3cm}\Rightarrow
 
\hspace{0.3cm}{k_1} =
 
-0.214 \cdot {k_0}\hspace{0.05cm},</math>
 
:<math> t = 0 \hspace{-0.1cm}  :  \hspace{0.2cm}g_0 = k_0 \cdot 1.000 + k_1 \cdot 2 \cdot
 
0.243= 1\hspace{0.3cm}\Rightarrow \hspace{0.3cm}0.896 \cdot {k_0}
 
= 1 \hspace{0.05cm}.</math>
 
  
[[File:P ID1425 Dig T 3 5 S2b version1.png|rechts|Eingangs- und Ausgangsimpuls des optimalen Nyquistentzerrers]]<br>
+
*The coefficients are thus obtained from the &nbsp;[[Signal_Representation/Fourier_Series|"Fourier series"]]&nbsp; (applied to the spectral function):
  
Daraus erhält man die optimalen Filterkoeffizienten <i>k</i><sub>0</sub> = 1.116 und <i>k</i><sub>1</sub> = 0.239. Das mittlere Diagramm zeigt, dass damit der erste Vorläufer und der erste Nachläufer kompensiert werden können und zugleich <i>g<sub>d</sub></i>(0) = 1 gilt (gelbe Hinterlegung). Die weiteren Detektionsgrundimpulswerte (blaue Kreise) sind aber von 0 verschieden und bewirken Impulsinterferenzen.<br><br>
+
:$$k_\lambda =T \cdot \int_{-1/(2T)}^{+1/(2T)}\frac{\cos(2 \pi f \lambda T)}  {\sum\limits_{\kappa = -\infty}^{+\infty}  |H_{\rm SK}(f -
 +
{\kappa}/{T})
 +
|^2} \hspace{0.2cm} {\rm d} f$$
 +
:$$ \hspace{0.25cm}\Rightarrow \hspace{0.25cm}H_{\rm TF}(f) =
 +
\sum\limits_{\lambda = -\infty}^{+\infty} k_\lambda \cdot {\rm
 +
e}^{-{\rm  j}2 \pi f \lambda T}\hspace{0.05cm}.$$
  
Das untere Diagramm zeigt, dass mit einem Filter zweiter Ordnung (<i>N</i> = 2) Nulldurchgänge bei &plusmn;<i>T</i> und bei &plusmn;2<i>T</i> erzwungen werden, wenn die Koeffizienten <i>k</i><sub>0</sub> = 1.127, <i>k</i><sub>1</sub> = 0.219 und <i>k</i><sub>2</sub> = 0.075 geeignet gewählt sind. Das Gleichungssystem zur Bestimmung der optimalen Koeffizienten lautet dabei:
+
The right graph shows the frequency response &nbsp;$20 \cdot \lg \ |H_{\rm E}(f)|$&nbsp; of the entire receiver filter including the matched filter.&nbsp; It holds:
  
:<math>t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0  = k_0 \cdot 1.000 + k_1 \cdot 2
+
:$$H_{\rm E}(f) = H_{\rm MF}(f) \cdot H_{\rm TF}(f) = \frac{H_{\rm SK}^{\star}(f)}{\sum\limits_{\kappa = -\infty}^{+\infty|H_{\rm SK}(f -
\cdot  0.243 + k_2 \cdot 2 \cdot 0.135 = 1\hspace{0.05cm},\\
+
{\kappa}/{T})
t= \pm T\hspace{-0.1cm}:\hspace{0.2cm}g_1  =  k_0 \cdot 0.243 + k_1 \cdot
+
|^2}.$$
[1.000+0.135]+ k_2  \cdot [0.243+0.086] = 0\hspace{0.05cm},
 
\\
 
t = \pm 2 T\hspace{-0.1cm}:\hspace{0.2cm}g_2 =  k_0 \cdot 0.135 + k_1 \cdot
 
[0.243+0.086]+ k_2 \cdot [1.000 + 0.059]= 0 \hspace{0.05cm}.</math>{{end}}<br>
 
  
Die Ergebnisse können wie folgt verallgemeinert werden:
+
To these representations it is to be noted:
*Mit einem Laufzeitfilter <i>N</i>&ndash;ter Ordnung können der Hauptwert <i>g<sub>d</sub></i>(0) zu 1 (normiert) sowie die ersten <i>N</i> Nachläufer und die ersten <i>N</i> Vorläufer zu Null gemacht werden.<br>
+
*For &nbsp;$a_\star = 0 \ \rm dB$&nbsp;  (ideal channel, green zero line)&nbsp; the transversal filter&nbsp; $H_{\rm TF}(f)$&nbsp; can be omitted and it is valid for NRZ rectangular pulses as already derived in the section&nbsp; [[Digital_Signal_Transmission/Error_Probability_for_Baseband_Transmission#Optimal_binary_receiver_.E2.80.93_.22Matched_Filter.22_realization|"Optimal binary receiver – "Matched Filter" realization"]]:&nbsp;  
 +
:$$H_{\rm E}(f) =H_{\rm S}(f) = {\rm sinc} (f T).$$
 +
*While the transversal filter frequency response &nbsp;$H_{\rm TF}(f)$&nbsp; is symmetrical to the Nyquist frequency &nbsp;$f_{\rm Nyq} = 1/(2T)$&nbsp; at &nbsp;$a_\star \ne 0 \ \rm dB$,&nbsp; this symmetry is no longer given for the receiver filter overall frequency response &nbsp;$H_{\rm E}(f)$.&nbsp; <br>
  
*Weitere Vor&ndash; und Nachläufer (|<i>&nu;</i>| > <i>N</i>) lassen sich so nicht kompensieren. Es ist auch möglich, dass diese außerhalb des Kompensationsbereichs vergrößert werden oder sogar neu entstehen.<br>
+
*The maxima of the frequency responses &nbsp;$H_{\rm TF}(f)$&nbsp; and &nbsp;$|H_{\rm E}(f)|$&nbsp; depend significantly on the characteristic cable attenuation &nbsp;$a_\star$.&nbsp; From the blue and red function curves, respectively,&nbsp; can be read:
 +
:$$a_{\star} = 40\,{\rm dB}\hspace{-0.1cm}:\hspace{0.2cm}{\rm Max}\big[H_{\rm
 +
TF}(f)\big]\hspace{0.1cm} \approx 80\,{\rm dB}, \hspace{0.2cm}{\rm
 +
Max}\big[\ |H_{\rm E}(f)| \  \big] \approx 40\,{\rm dB}\hspace{0.05cm},$$
 +
:$$a_{\star} = 80\,{\rm dB}\hspace{-0.1cm}:\hspace{0.2cm}{\rm Max}\big[H_{\rm TF}(f)\big]
 +
\approx 160\,{\rm dB}, \hspace{0.2cm}{\rm Max}\big[\ |H_{\rm E}(f)|\ \big]
 +
\approx 80\,{\rm dB}\hspace{0.05cm}.$$
  
*Im Grenzübergang <i>N</i> &#8594; &#8734; (in der Praxis heißt das: ein Filter mit sehr vielen Koeffizienten) ist eine vollständige Nyquistentzerrung und damit eine impulsinterferenzfreie Übertragung möglich.<br>
 
  
== Beschreibung im Frequenzbereich (1) ==
+
== Approximation of the optimal Nyquist equalizer ==
 
<br>
 
<br>
Die Tatsache, dass sich der optimale Nyquistentzerrer multiplikativ aus
+
We now consider the overall frequency response between the Dirac source and the decision.
*dem Matched&ndash;Filter <i>H</i><sub>MF</sub>(<i>f</i>) = <i>H</i><sub>S</sub><sup>&#8727;</sup>(<i>f</i>) &middot; <i>H</i><sub>K</sub><sup>&#8727;</sup>(<i>f</i>) &ndash; also angepasst an den Empfangsgrundimpuls &ndash;<br>
+
*This is made up multiplicatively of the frequency responses of the transmitter, channel and receiver.
 +
*According to the derivation, the overall frequency response must satisfy the Nyquist condition:
 +
[[File:P ID1428 Dig T 3 5 S3c version1.png|right|frame|Optimum overall Nyquist frequency response for a coaxial cable system|class=fit]]
 +
 
 +
:$$H_{\rm Nyq}(f) = H_{\rm S}(f) \cdot H_{\rm K}(f) \cdot H_{\rm E}(f) =
 +
\frac{|H_{\rm SK}(f)|^2}{\sum\limits_{\kappa = -\infty}^{+\infty}  |H_{\rm SK}(f -
 +
{\kappa}/{T})
 +
|^2}\hspace{0.05cm}.$$
 +
 
  
*und einem Transversalfilter <i>H</i><sub>TF</sub>(<i>f</i>) mit unendlich vielen Filterkoeffizienten<br><br>
+
The graph shows the following properties of the&nbsp; '''optimal Nyquist equalizer'''&nbsp; $\rm (ONE)$:
 +
*If the cable attenuation is sufficiently large &nbsp;$(a_\star \ge 10 \ \rm dB)$,&nbsp; the overall frequency response can be described with good approximation by the &nbsp;[[Digital_Signal_Transmission/Properties_of_Nyquist_Systems#1.2FT_Nyquist_spectra| "cosine rolloff low-pass"]].&nbsp; <br>
  
zusammensetzt, folgt aus dem ersten Nyquistkriterium. Durch Anwendung der <i>Variationsrechnung</i> erhält man den Frequenzgang des Transversalfilters (siehe Söder, G.; Tröndle, K.: ''Digitale Übertragungssysteme - Theorie, Optimierung & Dimensionierung der Basisbandsysteme.'' Berlin – Heidelberg: Springer, 1985.):
+
*The larger &nbsp;$a_\star$&nbsp; is,&nbsp; the smaller is the rolloff factor &nbsp;$r$&nbsp; and the steeper is the edge drop.&nbsp; For the characteristic cable attenuation &nbsp;$a_\star = 40 \ \rm dB$&nbsp; (blue curve)&nbsp; we get &nbsp;$r \approx 0.4$, for &nbsp;$a_\star = 80 \ \rm dB$&nbsp; (red curve)  $r \approx 0.18$.<br>
  
:<math>H_{\rm TF}(f) = \frac{1}{\sum\limits_{\kappa = -\infty}^{+\infty}  |H_{\rm SK}(f -
+
*Above the frequency &nbsp;$f_{\rm Nyq} \cdot (1 + r)$,&nbsp; &nbsp;$H_{\rm Nyq}(f)$&nbsp; has no components.&nbsp; However,&nbsp; with ideal channel &nbsp; &rArr; &nbsp; &nbsp;$a_\star = 0 \ \rm dB$&nbsp; (green curve), &nbsp;$H_{\rm Nyq}(f)= {\rm sinc}^2(f T)$&nbsp; theoretically extends to infinity.
\frac{\kappa}{T})
 
  |^2} \hspace{0.3cm}{\rm{mit}}\hspace{0.3cm}H_{\rm SK}(f) = H_{\rm S}(f)\cdot H_{\rm K}(f)
 
\hspace{0.05cm}.</math>
 
  
Die Grafik zeigt diesen Verlauf in logarithmierter Form für rechteckförmige NRZ&ndash;Sendeimpulse und ein Koaxialkabel mit der charakteristischen Kabeldämpfung
 
*<i>a</i><sub>&#8727;</sub> = 0 dB &nbsp;&#8658;&nbsp; grüne Null&ndash;Linie,<br>
 
*<i>a</i><sub>&#8727;</sub> = 40 dB &nbsp;&#8658;&nbsp; blauer Funktionsverlauf,<br>
 
*<i>a</i><sub>&#8727;</sub> = 80 dB &nbsp;&#8658;&nbsp; roter Funktionsverlauf.<br><br>
 
  
[[File:P ID1426 Dig T 3 5 S3 version1.png|Logarithmierter Frequenzgang des Transversalfilters|class=fit]]<br>
+
The interactive applet&nbsp; [[Applets:Frequency_%26_Impulse_Responses|"Frequency & Impulse Responses"]]&nbsp; illustrates,&nbsp; among other things,&nbsp; the properties of the&nbsp; "cosine rolloff low&ndash;pass".
  
Man erkennt aus obiger Gleichung und dieser Skizze:
 
*<i>H</i><sub>TF</sub>(<i>f</i>) ist reell, woraus sich die symmetrische Struktur des Transversalfilters ergibt: <i>k</i><sub>&ndash;&lambda;</sub> = <i>k</i><sub>&lambda;</sub>.<br>
 
  
*<i>H</i><sub>TF</sub>(<i>f</i>) ist eine mit der Frequenz 1/<i>T</i> periodische Funktion.<br>
+
== Calculation of the normalized noise power ==
 +
<br>
 +
We now consider the (normalized) noise power at the decision. For this holds:
  
*Die Koeffizienten ergeben sich somit aus der Fourierreihe (angewandt auf die Spektralfunktion):
+
:$$\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = \frac{\sigma_d^2}{N_0/
 +
(2T)} =T \cdot \int_{-1/(2T)}^{+1/(2T)} |H_{\rm E}(f)|^2
 +
\,{\rm d} f .$$
  
::<math>k_\lambda =T \cdot \int_{-1/(2T)}^{+1/(2T)}\frac{\cos(2 \pi f \lambda T)}  {\sum\limits_{\kappa = -\infty}^{+\infty}  |H_{\rm SK}(f -
+
[[File:P ID1429 Dig T 3 5 S5 version1.png|right|frame|To calculate the normalized noise power at the optimal Nyquist equalizer&nbsp; $\rm (ONE)$|class=fit]]
{\kappa}/{T})
+
*The left plot shows &nbsp;$|H_{\rm E}(f)|^2$&nbsp; in linear scale for the characteristic cable attenuation &nbsp;$a_\star = 80 \ \rm dB$.&nbsp; Note that &nbsp;$|H_{\rm E}(f = 0)|^2 = 1$.&nbsp;
|^2} \hspace{0.2cm} {\rm d} f \hspace{0.25cm}\Rightarrow \hspace{0.25cm}H_{\rm TF}(f) =
 
\sum\limits_{\lambda = -\infty}^{+\infty} k_\lambda \cdot {\rm
 
e}^{-{\rm  j}2 \pi f \lambda T}\hspace{0.05cm}.</math>
 
  
Die Bildbeschreibung wird auf der nächsten Seite fortgesetzt.<br>
+
*Since the frequency has been normalized to &nbsp;$1/T$&nbsp; in this plot,&nbsp; the normalized noise power corresponds exactly to the area&nbsp; (highlighted in red)&nbsp; under this curve.&nbsp; The numerical evaluation results in:
  
== Beschreibung im Frequenzbereich (2) ==
+
:$$\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = 1.68 \cdot 10^7\hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm
<br>
+
lg}\hspace{0.1cm}\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 \approx
Die linke Grafik zeigt den Verlauf 20 &middot; lg <i>H</i><sub>TF</sub>(<i>f</i>) im Bereich | <i>f</i> | &#8804; 1/<i>T</i>. Rechts ist der Frequenzgang 20 &middot; lg |<i>H</i><sub>E</sub>(<i>f</i>)| des gesamten Empfangsfilters einschließlich Matched&ndash;Filter dargestellt. Es gilt:
+
72.25\,{\rm dB} \hspace{0.05cm}.$$
  
:<math>H_{\rm E}(f) = H_{\rm MF}(f) \cdot H_{\rm TF}(f) = \frac{H_{\rm SK}^{^\star}(f)}{\sum\limits_{\kappa = -\infty}^{+\infty} |H_{\rm SK}(f -
+
*It can be shown that the normalized noise power can be calculated using the transversal filter frequency response &nbsp;$H_{\rm TF}(f)$&nbsp; alone, as shown in the right graph:
{\kappa}/{T})
+
:$$\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = T \cdot
|^2}.</math>
+
\int_{-1/(2T)}^{+1/(2T)} H_{\rm TF}(f) \,{\rm d} f
 +
\hspace{0.3cm}(= k_0)\hspace{0.05cm}.$$
  
[[File:P ID1427 Dig T 3 5 S3b version1.png|Frequenzgang des optimalen Nyquistentzerrers|class=fit]]<br>
+
*The red areas are exactly the same in both images.
 +
<br clear=all>
 +
{{BlaueBox|TEXT= 
 +
$\text{Conclusion:}$&nbsp; The normalized noise power of the optimal Nyquist equalizer is equal to the Fourier coefficient &nbsp;$k_0$ when the real, symmetric, and periodic transversal filter frequency response &nbsp;$H_{\rm TF}(f)$&nbsp; is represented as a Fourier series.
  
Zu diesen Darstellungen ist anzumerken:
+
[[File:P ID1430 Dig T 3 5 S5b version3.png|right|frame|Coefficients of the optimal Nyquist equalizer&nbsp; $\rm (ONE)$|class=fit]]
*Der Transversalfilter&ndash;Frequenzgang <i>H</i><sub>TF</sub>(<i>f</i>) ist  symmetrisch zur Nyquistfrequenz <i>f</i><sub>Nyq</sub> = 1/(2<i>T</i>). Diese Symmetrie ist beim Empfangsfilter&ndash;Gesamtfrequenzgang <i>H</i><sub>E</sub>(<i>f</i>) nicht mehr gegeben.<br>
+
*In the second column of the table, &nbsp;$10 \cdot \lg  \ (k_0)$&nbsp; is given depending on the characteristic cable attenuation &nbsp;$a_\star$&nbsp; of a coaxial cable.
*Die Maxima der Frequenzgänge <i>H</i><sub>TF</sub>(<i>f</i>) und |<i>H</i><sub>E</sub>(<i>f</i>)| hängen signifikant von der charakteristischen Kabeldämpfung ab. Es gilt:
 
::<math>a_{\star} = 40\,{\rm dB}\hspace{-0.1cm}:\hspace{0.2cm}{\rm Max}[H_{\rm
 
TF}(f)]\hspace{0.1cm} \approx 80\,{\rm dB}, \hspace{0.2cm}{\rm
 
Max}[|H_{\rm E}(f)|] \approx 40\,{\rm dB}\hspace{0.05cm},</math>
 
::<math>a_{\star} = 80\,{\rm dB}\hspace{-0.1cm}:\hspace{0.2cm}{\rm Max}[H_{\rm TF}(f)]
 
\approx 160\,{\rm dB}, \hspace{0.2cm}{\rm Max}[|H_{\rm E}(f)|]
 
\approx 80\,{\rm dB}\hspace{0.05cm}.</math>
 
  
Für <i>a</i><sub>&#8727;</sub> = 0 dB (idealer Kanal) kann auf das Transversalfilter verzichtet werden und es gilt, wie bereits im [http://en.lntwww.de/Digitalsignal%C3%BCbertragung/Fehlerwahrscheinlichkeit_bei_Basisband%C3%BCbertragung#Optimaler_Bin.C3.A4rempf.C3.A4nger_-_Realisierung_mit_Matched-Filter_.281.29 Kapitel 1.2] hergeleitet:
+
*Due to the chosen normalization, the table is also valid for&nbsp; [[Digital_Signal_Transmission/Intersymbol_Interference_for_Multi-Level_Transmission#Eye_opening_for_redundancy-free_multi-level_systems|"redundancy-free multi-level systems"]];&nbsp;  here &nbsp;$M$&nbsp; denotes the level number.<br>
  
:<math>H_{\rm E}(f) =H_{\rm S}(f) = {\rm si} (\pi f T)\hspace{0.05cm}.</math>
+
*The coefficients &nbsp;$k_1$, &nbsp;$k_2$, &nbsp;$k_3$, ... of the transversal filter have alternating signs for &nbsp;$a_\star \ne 0 \ \rm dB$.&nbsp;
 +
 +
*For &nbsp;$a_\star = 40 \ \rm dB$,&nbsp; four coefficients are greater in magnitude than &nbsp;$k_0/10$,&nbsp; and for &nbsp;$a_\star = 80 \ \rm dB$&nbsp; even seven.}}
  
== Approximation des optimalen Nyquistentzerrers ==
+
== Comparison based on the system efficiency ==
 
<br>
 
<br>
Betrachten wir nun den Gesamtfrequenzgang zwischen der Diracquelle und dem Entscheider. Dieser setzt sich multiplikativ aus den Frequenzgängen von Sender, Kanal und Empfänger zusammen. Entsprechend der Herleitung muss der Gesamtfrequenzgang die Nyquistbedingung erfüllen:
+
For a system comparison, the &nbsp;[[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_power_limitation|"system efficiency"]]&nbsp; is suitable,&nbsp; which relates the achievable detection SNR &nbsp;$\rho_d$&nbsp; to the maximum SNR &nbsp;$\rho_{d, \ {\rm max}}$,&nbsp; which,&nbsp; however,&nbsp; is only achievable for ideal channel &nbsp;$H_{\rm K}(f) \equiv 1$.&nbsp;
  
:<math>H_{\rm Nyq}(f) = H_{\rm S}(f) \cdot H_{\rm K}(f) \cdot H_{\rm E}(f) =
+
[[File:EN_Dig_T_3_5_S6_neu.png|right|frame|Comparison of binary and multi-level transmission systems according to &nbsp;$\text{GLP}$&nbsp; and &nbsp;$\text{ONE}$|class=fit]]
\frac{|H_{\rm SK}(f)|^2}{\sum\limits_{\kappa = -\infty}^{+\infty} |H_{\rm SK}(f -
+
For the system efficiency, with &nbsp;$M$&ndash;level transmission and optimal Nyquist equalization:
{\kappa}/{T})
+
:$$\eta = \frac{\rho_d}{s_0^2 \cdot T / N_0}=\frac{{\rm log_2}\hspace{0.1cm}M}{(M-1)^2 \cdot k_0}.$$
|^2}\hspace{0.05cm}.</math>
 
  
Die Grafik zeigt folgende Eigenschaften des optimalen Nyquistfilters:
+
*The&nbsp; (normalized)&nbsp; noise power &nbsp;$k_0$&nbsp; can be read from the &nbsp;[[Digital_Signal_Transmission/Linear_Nyquist_Equalization#Calculation_of_the_normalized_noise_power|'''table''']]&nbsp; in the last section.  
*Ist die Kabeldämpfung hinreichend groß (<i>a</i><sub>&#8727;</sub> > 10 dB), so kann der Gesamtfrequenzgang mit sehr guter Näherung durch einen Cosinus&ndash;Rolloff&ndash;Tiefpass beschrieben werden.<br>
 
  
*Je größer <i>a</i><sub>&#8727;</sub> ist, desto kleiner ist der Rolloff&ndash;Faktor und um so steiler verläuft der Flankenabfall. Für die charakteristische Kabeldämpfung <i>a</i><sub>&#8727;</sub> = 40 dB ergibt sich <i>r</i> &asymp; 0.4, für 80 dB ist <i>r</i> &asymp; 0.18.<br>
+
*Note the normalization of the characteristic cable attenuation &nbsp;$a_\star$&nbsp; in the first column.  
  
*Oberhalb der Frequenz <i>f</i><sub>Nyq</sub> &middot; (1 + <i>r</i>) besitzt <i>H</i><sub>Nyq</sub>(<i>f</i>) keine Anteile. Bei idealem Kanal &ndash; also für <i>a</i><sub>&#8727;</sub> = 0 dB &ndash;  reicht <i>H</i><sub>Nyq</sub>(<i>f</i>) = si<sup>2</sup>(&pi;<i>f</i><i>T</i>) allerdings theoretisch bis ins Unendliche (grüne Kurve).
+
*The table on the right from&nbsp; [TS87]<ref name='TS87'/>&nbsp; allows a system comparison for the characteristic cable attenuation &nbsp;$a_\star = 80 \ \rm dB$.  
  
:[[File:P ID1428 Dig T 3 5 S3c version1.png|Optimaler Nyquistfrequenzgang|class=fit]]<br>
 
  
Mit dem folgenden Interaktionsmodul können Sie sich den Cosinus&ndash;Rolloff&ndash;Tiefpass im Frequenz&ndash; und Zeitbereich verdeutlichen:<br>
+
Compared are:  
[[:File:tiefpass.swf|Tiefpässe im Frequenz- und Zeitbereich]]<br>
 
  
 +
* the [[Digital_Signal_Transmission/Berücksichtigung_von_Kanalverzerrungen_und_Entzerrung|"Gaussian overall frequency response"]] &nbsp;$\text{(GLP)}$,&nbsp; which leads to an intersymbol interference system even when optimized, <br>
  
 +
*the &nbsp;[[Digital_Signal_Transmission/Linear_Nyquist_Equalization#Structure_of_the_optimal_Nyquist_equalizer|"optimal Nyquist equalizer"]] &nbsp;$\text{(ONE)}$; here,&nbsp; intersymbol interference is excluded per se.
 +
<br clear=all>
 +
{{BlaueBox|TEXT= 
 +
$\text{Conclusion:}$&nbsp; The results of this system comparison can be summarized as follows:
 +
#In the binary case &nbsp;$(M = 2)$,&nbsp; the intersymbol interference-free system &nbsp;$\text{(ONE)}$&nbsp; outperforms the intersymbol interference system &nbsp;$\text{(GLP)}$ by about &nbsp;$6 \ \rm dB$.&nbsp; <br>
 +
#If the optimal Nyquist equalization is applied to multi-level systems, a further, significant gain in signal-to-noise ratio is possible compared to &nbsp;$\text{GLP}$.&nbsp;
 +
#For &nbsp;$M =4$,&nbsp; this gain is about &nbsp;$18.2 \ \rm dB$.<br>
 +
#However, the narrowband &nbsp;$\text{GLP}$ system can be significantly improved by using a receiver with decision feedback. This will be discussed in the next chapter.}}<br>
  
 +
&rArr; &nbsp; At this point we refer to the&nbsp; (German language)&nbsp; SWF applet&nbsp; [[Applets:Lineare_Nyquistentzerrung|"Lineare Nyquistentzerrung"]] &nbsp; &rArr; &nbsp; "Linear Nyquist Equalization".
  
  
  
 +
==Exercises for the chapter==
 +
<br>
 +
[[Aufgaben:Exercise_3.6:_Transversal_Filter_of_the_Optimal_Nyquist_Equalizer| Exercise 3.6: Transversal Filter of the Optimal Nyquist Equalizer]]
  
 +
[[Aufgaben:Exercise_3.6Z:Optimum_Nyquist_Equalizer_for_Exponential_Pulse| Exercise 3.6Z: Optimum Nyquist Equalizer for Exponential Pulse]]
  
 +
[[Aufgaben:Exercise_3.7:_Optimal_Nyquist_Equalization_once_again|Exercise 3.7: Optimal Nyquist Equalization once again]]
  
 +
[[Aufgaben:Exercise_3.7Z:_Regenerator_Field_Length|Exercise 3.7Z: Regenerator Field Length]]
  
 +
==References==
  
 +
<references/>
  
  
 
{{Display}}
 
{{Display}}

Latest revision as of 11:21, 13 July 2022

Structure of the optimal Nyquist equalizer


In this section we assume the following block diagram of a binary system.  In this regard,  it should be noted:

Block diagram of the optimal Nyquist equalizer
  • The  "Dirac source"  provides the message to be transmitted in binary bipolar form   ⇒   amplitude coefficients  $a_\nu \in \{ -1, \hspace{0.05cm}+1\}$.  The source is assumed to be redundancy-free.
  • The  "transmission pulse shape"  $g_s(t)$  is taken into account by the transmitter frequency response  $H_{\rm S}(f)$.  Mostly,  $H_{\rm S}(f) = {\rm sinc}(f T)$  is based   ⇒   NRZ rectangular transmission pulses.
  • In some derivations,  transmitter and channel are combined by the  "common frequency response"  $H_{\rm SK}(f) = H_{\rm S}(f) \cdot H_{\rm K}(f)$. 
  • The receiver filter  $H_{\rm E}(f)$  is multiplicatively composed of the  matched filter  $H_{\rm MF}(f) = H_{\rm SK}^\star(f)$  and the  transversal filter  $H_{\rm TF}(f)$,  at least it can be split up mentally in this way.
  • The overall frequency response between Dirac source and threshold decision should satisfy the   "first Nyquist condition".  Thus, it must hold:
$$H_{\rm S}(f) \cdot H_{\rm K}(f) \cdot H_{\rm MF}(f) \cdot H_{\rm TF}(f) = H_{\rm Nyq}(f) \hspace{0.05cm}.$$
$$\rho_d = \frac{2 \cdot s_0^2 \cdot T}{\sigma_d^2} = \frac{2 \cdot s_0^2 \cdot T}{N_0}\cdot \frac{1}{\sigma_{d,\hspace{0.05cm} {\rm norm}}^2} \hspace{0.3cm}\Rightarrow \hspace{0.3cm} \eta = \frac{\rho_d }{\rho_{d,\hspace{0.05cm} {\rm max}}} = \frac{\rho_d }{2 \cdot s_0^2 \cdot T/N_0} = \frac{1}{\sigma_{d,\hspace{0.05cm} {\rm norm}}^2} \hspace{0.05cm}.$$
  • The optimization task is therefore limited to determining the receiver filter  $H_{\rm E}(f)$  such
    that the normalized noise power before the decision takes the smallest possible value:
\[\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = \frac{\sigma_d^2}{N_0/ T} =T \cdot \int_{-\infty}^{+\infty} |H_{\rm E}(f)|^2 \,{\rm d} f \stackrel {!}{=} {\rm minimum}\hspace{0.05cm}.\]

$\text{Definition:}$  We refer to the configuration described here as  Optimal Nyquist Equalization  $\rm (ONE)$.


Although this can also – and especially effectively – be applied to multi-level systems, we initially set  $M = 2$.

Operating principle of the transversal filter

Second order transversal filter as part of the optimal Nyquist equalizer


Let us first clarify the task of the symmetric transversal filter with frequency response

$$H_{\rm TF}(f) \hspace{0.4cm}\bullet\!\!-\!\!\!-\!\!\!-\!\!\circ \hspace{0.4cm} h_{\rm TF}(t) = \sum_{\lambda = -N}^{+N} k_\lambda \cdot \delta(t - \lambda \cdot T) $$

and the following properties:

  • $N$  indicates the  "order"  of the filter   ⇒   the graph shows a second order filter  $(N=2)$.
  • For the filter coefficients  $k_{-\lambda} = k_{\lambda}$   ⇒   symmetric structure   ⇒   $H_{\rm TF}(f)$ is real.
  • $H_{\rm TF}(f)$  is thus completely determined by the coefficients  $k_0$, ... , $k_N$.


For the input pulse  $g_m(t)$  we assume without restriction of generality that it

  • is symmetric about  $t=0$  (output of the matched filter),
  • has the value  $g_m(\nu)$  at times  $\nu \cdot T$  and  $-\nu \cdot T$,  respectively.


Thus,  the input pulse values are:

$$\text{...}\hspace{0.2cm} , g_m(3),\hspace{0.15cm}g_m(2),\hspace{0.15cm}g_m(1),\hspace{0.15cm}\hspace {0.15cm}g_m(0),\hspace{0.15cm}g_m(1),\hspace{0.15cm}g_m(2),\hspace{0.15cm}g_m(3),\hspace{0.1cm} \text{...}\hspace{0.05cm}.$$

Consequently,  for the basic detection pulse  $g_d(t)$  at the filter output, the following values result at the time instants  $\nu \cdot T$  with the abbreviations  $g_0 =g_d(t= 0)$,   $g_1 =g_d(t= \pm T)$,   $g_2 =g_d(t= \pm 2T)$: 

$$ t = 0\hspace{-0.1cm}:\hspace{0.9cm}g_0 = k_0 \cdot g_m(0) + k_1 \cdot 2 \cdot g_m(1) \hspace{1.23cm}+k_2 \cdot 2 \cdot g_m(2),\hspace{0.05cm} $$
$$ t = \pm T\hspace{-0.1cm}:\hspace{0.45cm}g_1 = k_0 \cdot g_m(1) + k_1 \cdot \big [g_m(0)+g_m(2)]+ k_2 \cdot [g_m(1)+g_m(3) \big ], $$
$$ t = \pm 2T\hspace{-0.1cm}:\hspace{0.2cm}g_2 = k_0 \cdot g_m(2) + k_1 \cdot \big [g_m(1)+g_m(3)\big ]+ k_2 \cdot \big [g_m(2)+g_m(4)\big ] \hspace{0.05cm}. $$

From this system with three linearly independent equations,  one can determine the filter coefficients  $k_0$,  $k_1$  and  $k_2$  in such a way that the basic detection pulse  $g_d(t)$  has the following interpolation points:

$$\text{...}\hspace{0.15cm} , g_3,\hspace{0.25cm}g_2 = 0 ,\hspace{0.15cm}g_1 = 0 ,\hspace{0.15cm}g_0 = 1,\hspace{0.15cm}g_1 = 0 ,\hspace{0.15cm}g_2 = 0 ,\hspace{0.25cm}g_3 ,\hspace{0.15cm} \text{...}$$

$\text{Example 1:}$  We assume the symmetrical input signal according to the upper diagram in the graph. With the abbreviation  $g_m(\nu)= g_m(\pm \nu \cdot T)$  there are the following samples at the distance of the symbol duration  $T$:

$$g_m(t) = {\rm e}^{ - \sqrt{2 \hspace{0.05cm} \cdot \hspace{0.05cm}\vert\hspace{0.05cm} t \hspace{0.05cm} \vert /T} }\hspace{0.3cm} \Rightarrow \hspace{0.3cm} g_m(0) = 1 ,\hspace{0.35cm}g_m(1)= 0.243,\hspace{0.35cm}g_m(2)= 0.135,\hspace{0.35cm}g_m(3)= 0.086, \hspace{0.35cm}g_m(4)= 0.059 \hspace{0.05cm}.$$

⇒   For the output pulse  $g_d(t =0) = 1$  and  $g_d(t =\pm T) = 0$  should be valid.  For this purpose,  a first-order delay filter with coefficients  $k_0$  and  $k_1$ is suitable,  which must satisfy the following conditions:

Input and output pulse of the
optimal Nyquist equalizer
$$t = \pm T\hspace{-0.1cm} : \hspace{0.2cm}g_1 = k_0 \cdot 0.243 + k_1 \cdot \big [1.000 +0.135 \big ] = 0\hspace{0.3cm}\Rightarrow \hspace{0.3cm}{k_1} = -0.214 \cdot {k_0}\hspace{0.05cm},$$
$$ t = 0 \hspace{-0.1cm} : \hspace{0.6cm}g_0 = k_0 \cdot 1.000 + k_1 \cdot 2 \cdot 0.243= 1\hspace{0.3cm}\Rightarrow \hspace{0.3cm}0.896 \cdot {k_0} = 1 \hspace{0.05cm}.$$

From this,  the optimal filter coefficients  $k_0 = 1.116$  and  $k_1 = 0.239$ are obtained.

  • The middle diagram shows that thus the first precursor and the first trailer can be compensated and at the same time  $g_d(0) =1$  is valid  (yellow background).
  • However,  the further basic detection pulse values (blue circles) are different from zero and cause intersymbol interference.

⇒   The lower diagram shows that with a second order filter  $(N = 2)$  zero crossings are forced at  $\pm T$  and at  $\pm 2T$  if the coefficients  $k_0 = 1.127$,  $k_1 = 0.219$  and  $k_2 = 0.075$  are suitably chosen. The system of equations for determining the optimal coefficients is thereby:

$$t = 0\hspace{-0.1cm}:\hspace{0.85cm}g_0 = k_0 \cdot 1.000 + k_1 \cdot 2 \cdot 0.243 + k_2 \cdot 2 \cdot 0.135 = 1\hspace{0.05cm},$$
$$t= \pm T\hspace{-0.1cm}:\hspace{0.45cm}g_1 = k_0 \cdot 0.243 + k_1 \cdot \big [1.000+0.135 \big ]+ k_2 \cdot \big [0.243+0.086 \big ] = 0\hspace{0.05cm},$$
$$t = \pm 2 T\hspace{-0.1cm}:\hspace{0.2cm}g_2 = k_0 \cdot 0.135 + k_1 \cdot \big [0.243+0.086\big ]+ k_2 \cdot \big [1.000 + 0.059 \big ]= 0 \hspace{0.05cm}.$$


$\text{Conclusion:}$  The results can be generalized as follows:

  1. With an  $N$–th order delay filter,  the main value can be made to  $g_d(0)=1$  (normalized).
  2. The first $N$  trailers  $g_{\nu}$  and the first $N$  precursors  $g_{-\nu}$  can be made to zero.
  3. Further precursors and trailers  $(\nu \gt N)$  cannot be compensated in this way. 
  4. It is even possible that the precursors and trailers outside the compensation range are enlarged or even new ones are created.
  5. In the limit  $N \to \infty$  (in practice this means:   a filter with very many coefficients)  a complete Nyquist equalization and thus an ISI-free transmission is possible.


Description in the frequency domain


The fact that the optimal Nyquist equalizer is multiplicatively derived from

  • the matched filter  $H_{\rm MF}(f) = H_{\rm S}^\star (f)\cdot H_{\rm K}^\star(f)$  – i.e. matched to the basic receiver pulse  $g_r(t)$  – and
  • a transversal filter  $H_{\rm MF}(f)$  with infinitely many filter coefficients

follows from the first Nyquist criterion.  By applying the  "Calculus of Variations",  the frequency response of the transversal filter is obtained   – see [TS87][1]:

Magnitude frequency response of the transversal filter  (left) and the entire optimal Nyquist equalizer  (right)

$$H_{\rm TF}(f) = \frac{1}{\sum\limits_{\kappa = -\infty}^{+\infty} |H_{\rm SK}(f - \frac{\kappa}{T}) |^2},$$ $$\text{where }H_{\rm SK}(f) = H_{\rm S}(f)\cdot H_{\rm K}(f).$$

The left graph shows  $20 \cdot \lg \ H_{\rm TF}(f)$  in the range  $| f | \le 1/T$. This assumes rectangular NRZ transmission pulses and a coaxial cable with the characteristic cable attenuation  $a_\star$.

One can see from the equation and the left graph:

  • $H_{\rm TF}(f)$  is  "real",  which results in the symmetrical structure of the transversal filter:   $k_{-\lambda} =k_{+\lambda} $.
  • $H_{\rm TF}(f)$  is at the same time   "periodic"  with frequency  $1/T$.
  • The coefficients are thus obtained from the  "Fourier series"  (applied to the spectral function):
$$k_\lambda =T \cdot \int_{-1/(2T)}^{+1/(2T)}\frac{\cos(2 \pi f \lambda T)} {\sum\limits_{\kappa = -\infty}^{+\infty} |H_{\rm SK}(f - {\kappa}/{T}) |^2} \hspace{0.2cm} {\rm d} f$$
$$ \hspace{0.25cm}\Rightarrow \hspace{0.25cm}H_{\rm TF}(f) = \sum\limits_{\lambda = -\infty}^{+\infty} k_\lambda \cdot {\rm e}^{-{\rm j}2 \pi f \lambda T}\hspace{0.05cm}.$$

The right graph shows the frequency response  $20 \cdot \lg \ |H_{\rm E}(f)|$  of the entire receiver filter including the matched filter.  It holds:

$$H_{\rm E}(f) = H_{\rm MF}(f) \cdot H_{\rm TF}(f) = \frac{H_{\rm SK}^{\star}(f)}{\sum\limits_{\kappa = -\infty}^{+\infty} |H_{\rm SK}(f - {\kappa}/{T}) |^2}.$$

To these representations it is to be noted:

$$H_{\rm E}(f) =H_{\rm S}(f) = {\rm sinc} (f T).$$
  • While the transversal filter frequency response  $H_{\rm TF}(f)$  is symmetrical to the Nyquist frequency  $f_{\rm Nyq} = 1/(2T)$  at  $a_\star \ne 0 \ \rm dB$,  this symmetry is no longer given for the receiver filter overall frequency response  $H_{\rm E}(f)$. 
  • The maxima of the frequency responses  $H_{\rm TF}(f)$  and  $|H_{\rm E}(f)|$  depend significantly on the characteristic cable attenuation  $a_\star$.  From the blue and red function curves, respectively,  can be read:
$$a_{\star} = 40\,{\rm dB}\hspace{-0.1cm}:\hspace{0.2cm}{\rm Max}\big[H_{\rm TF}(f)\big]\hspace{0.1cm} \approx 80\,{\rm dB}, \hspace{0.2cm}{\rm Max}\big[\ |H_{\rm E}(f)| \ \big] \approx 40\,{\rm dB}\hspace{0.05cm},$$
$$a_{\star} = 80\,{\rm dB}\hspace{-0.1cm}:\hspace{0.2cm}{\rm Max}\big[H_{\rm TF}(f)\big] \approx 160\,{\rm dB}, \hspace{0.2cm}{\rm Max}\big[\ |H_{\rm E}(f)|\ \big] \approx 80\,{\rm dB}\hspace{0.05cm}.$$


Approximation of the optimal Nyquist equalizer


We now consider the overall frequency response between the Dirac source and the decision.

  • This is made up multiplicatively of the frequency responses of the transmitter, channel and receiver.
  • According to the derivation, the overall frequency response must satisfy the Nyquist condition:
Optimum overall Nyquist frequency response for a coaxial cable system
$$H_{\rm Nyq}(f) = H_{\rm S}(f) \cdot H_{\rm K}(f) \cdot H_{\rm E}(f) = \frac{|H_{\rm SK}(f)|^2}{\sum\limits_{\kappa = -\infty}^{+\infty} |H_{\rm SK}(f - {\kappa}/{T}) |^2}\hspace{0.05cm}.$$


The graph shows the following properties of the  optimal Nyquist equalizer  $\rm (ONE)$:

  • If the cable attenuation is sufficiently large  $(a_\star \ge 10 \ \rm dB)$,  the overall frequency response can be described with good approximation by the   "cosine rolloff low-pass"
  • The larger  $a_\star$  is,  the smaller is the rolloff factor  $r$  and the steeper is the edge drop.  For the characteristic cable attenuation  $a_\star = 40 \ \rm dB$  (blue curve)  we get  $r \approx 0.4$, for  $a_\star = 80 \ \rm dB$  (red curve) $r \approx 0.18$.
  • Above the frequency  $f_{\rm Nyq} \cdot (1 + r)$,   $H_{\rm Nyq}(f)$  has no components.  However,  with ideal channel   ⇒    $a_\star = 0 \ \rm dB$  (green curve),  $H_{\rm Nyq}(f)= {\rm sinc}^2(f T)$  theoretically extends to infinity.


The interactive applet  "Frequency & Impulse Responses"  illustrates,  among other things,  the properties of the  "cosine rolloff low–pass".


Calculation of the normalized noise power


We now consider the (normalized) noise power at the decision. For this holds:

$$\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = \frac{\sigma_d^2}{N_0/ (2T)} =T \cdot \int_{-1/(2T)}^{+1/(2T)} |H_{\rm E}(f)|^2 \,{\rm d} f .$$
To calculate the normalized noise power at the optimal Nyquist equalizer  $\rm (ONE)$
  • The left plot shows  $|H_{\rm E}(f)|^2$  in linear scale for the characteristic cable attenuation  $a_\star = 80 \ \rm dB$.  Note that  $|H_{\rm E}(f = 0)|^2 = 1$. 
  • Since the frequency has been normalized to  $1/T$  in this plot,  the normalized noise power corresponds exactly to the area  (highlighted in red)  under this curve.  The numerical evaluation results in:
$$\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = 1.68 \cdot 10^7\hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 \approx 72.25\,{\rm dB} \hspace{0.05cm}.$$
  • It can be shown that the normalized noise power can be calculated using the transversal filter frequency response  $H_{\rm TF}(f)$  alone, as shown in the right graph:
$$\sigma_{d,\hspace{0.05cm} {\rm norm}}^2 = T \cdot \int_{-1/(2T)}^{+1/(2T)} H_{\rm TF}(f) \,{\rm d} f \hspace{0.3cm}(= k_0)\hspace{0.05cm}.$$
  • The red areas are exactly the same in both images.


$\text{Conclusion:}$  The normalized noise power of the optimal Nyquist equalizer is equal to the Fourier coefficient  $k_0$ when the real, symmetric, and periodic transversal filter frequency response  $H_{\rm TF}(f)$  is represented as a Fourier series.

Coefficients of the optimal Nyquist equalizer  $\rm (ONE)$
  • In the second column of the table,  $10 \cdot \lg \ (k_0)$  is given depending on the characteristic cable attenuation  $a_\star$  of a coaxial cable.
  • The coefficients  $k_1$,  $k_2$,  $k_3$, ... of the transversal filter have alternating signs for  $a_\star \ne 0 \ \rm dB$. 
  • For  $a_\star = 40 \ \rm dB$,  four coefficients are greater in magnitude than  $k_0/10$,  and for  $a_\star = 80 \ \rm dB$  even seven.

Comparison based on the system efficiency


For a system comparison, the  "system efficiency"  is suitable,  which relates the achievable detection SNR  $\rho_d$  to the maximum SNR  $\rho_{d, \ {\rm max}}$,  which,  however,  is only achievable for ideal channel  $H_{\rm K}(f) \equiv 1$. 

Comparison of binary and multi-level transmission systems according to  $\text{GLP}$  and  $\text{ONE}$

For the system efficiency, with  $M$–level transmission and optimal Nyquist equalization:

$$\eta = \frac{\rho_d}{s_0^2 \cdot T / N_0}=\frac{{\rm log_2}\hspace{0.1cm}M}{(M-1)^2 \cdot k_0}.$$
  • The  (normalized)  noise power  $k_0$  can be read from the  table  in the last section.
  • Note the normalization of the characteristic cable attenuation  $a_\star$  in the first column.
  • The table on the right from  [TS87][1]  allows a system comparison for the characteristic cable attenuation  $a_\star = 80 \ \rm dB$.


Compared are:


$\text{Conclusion:}$  The results of this system comparison can be summarized as follows:

  1. In the binary case  $(M = 2)$,  the intersymbol interference-free system  $\text{(ONE)}$  outperforms the intersymbol interference system  $\text{(GLP)}$ by about  $6 \ \rm dB$. 
  2. If the optimal Nyquist equalization is applied to multi-level systems, a further, significant gain in signal-to-noise ratio is possible compared to  $\text{GLP}$. 
  3. For  $M =4$,  this gain is about  $18.2 \ \rm dB$.
  4. However, the narrowband  $\text{GLP}$ system can be significantly improved by using a receiver with decision feedback. This will be discussed in the next chapter.


⇒   At this point we refer to the  (German language)  SWF applet  "Lineare Nyquistentzerrung"   ⇒   "Linear Nyquist Equalization".


Exercises for the chapter


Exercise 3.6: Transversal Filter of the Optimal Nyquist Equalizer

Exercise 3.6Z: Optimum Nyquist Equalizer for Exponential Pulse

Exercise 3.7: Optimal Nyquist Equalization once again

Exercise 3.7Z: Regenerator Field Length

References

  1. 1.0 1.1 Tröndle, K.; Söder, G.:  Optimization of Digital Transmission Systems.  Boston – London: Artech House, 1987,  ISBN:  0-89006-225-0.