Difference between revisions of "Aufgaben:Exercise 3.3Z: Optimization of a Coaxial Cable System"

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{{quiz-Header|Buchseite=Digitalsignalübertragung/Ber%C3%BCcksichtigung_von_Kanalverzerrungen_und_Entzerrung
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{{quiz-Header|Buchseite=Digital_Signal_Transmission/Consideration_of_Channel_Distortion_and_Equalization
 
}}
 
}}
  
[[File:P_ID1409__Dig_Z_3_3.png|right|frame]]
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[[File:P_ID1409__Dig_Z_3_3.png|right|frame|Normalized system parameters for different cutoff frequencies]]
 +
We consider a redundancy-free binary transmission system with the following specifications:
 +
* The transmission pulses are NRZ rectangular and have energy  $E_{\rm B} = s_0^2 \cdot T$.
 +
 +
* The channel is a coaxial cable with characteristic cable attenuation  $a_* = 40 \, {\rm dB}$.
  
===Fragebogen===
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* AWGN noise with (one-sided) noise power density  $N_0 = 0.0001 \cdot E_{\rm B}$  is present.
 +
 
 +
* The receiver frequency response  $H_{\rm E}(f)$  includes an ideal channel equalizer  $H_{\rm K}^{\rm -1}(f)$  and a Gaussian low-pass filter  $H_{\rm G}(f)$  with cutoff frequency  $f_{\rm G}$  for noise power limitation.
 +
 
 +
 
 +
The table shows the eye opening   $\ddot{o}(T_{\rm D})$   as well as the detection noise rms value   $\sigma_{\rm d}$   – each normalized to the transmitted amplitude  $s_0$  – for different cutoff frequencies  $f_{\rm G}$.  The cutoff frequency is to be chosen such that the worst-case error probability is as small as possible,  with the following definition:
 +
:$$p_{\rm U} = {\rm Q} \left( \frac{\ddot{o}(T_{\rm D})/2}{ \sigma_d}
 +
  \right) \hspace{0.3cm}\Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q} \left( \sqrt{\rho_{\rm U}}\right)$$
 +
 
 +
*This quantity represents an upper bound for the mean error probability    $p_{\rm S} \le p_{\rm U}$.
 +
 +
*For  $f_{\rm G} \cdot T ≥ 0.4$,  a lower bound can also be given:    $p_{\rm S} \ge p_{\rm U}/4$.
 +
 
 +
 
 +
 
 +
Notes:
 +
*The exercise belongs to the chapter  [[Digital_Signal_Transmission/Consideration_of_Channel_Distortion_and_Equalization|"Consideration of Channel Distortion and Equalization"]].
 +
 
 +
* Use the interaction module  [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen|"Complementary Gaussian Error Functions"]]  for numerical evaluation of the Q-function.
 +
 +
 
 +
 
 +
 
 +
===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{Multiple-Choice
+
{Within the given grid,&nbsp; determine the optimal cutoff frequency with respect to the&nbsp; "worst-case error probability"&nbsp; criterion.
|type="[]"}
+
|type="{}"}
+ correct
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$f_\text{G, opt} \cdot T \  = \ $  { 0.4 3% }
- false
 
  
{Input-Box Frage
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{What values does this give for the&nbsp; "worst-case signal-to-noise ratio"&nbsp; and the worst-case error probability?
 
|type="{}"}
 
|type="{}"}
$xyz$ = { 5.4 3% } $ab$
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$f_\text{G} = \text{G, opt:}\hspace{0.4cm} 10 \cdot {\rm lg} \, \rho_{\rm U}  \  = \ $ { 5.41 3% } ${\ \rm dB}$
 +
$\hspace{4.07cm}p_{\rm U}  \  = \ $ { 3.1 3% } $\ \rm \%$
 +
 
 +
{To what value would we need to reduce the noise power density &nbsp;$N_0$&nbsp; (with respect to signal energy)&nbsp; so that &nbsp;$p_{\rm U}$&nbsp; is not greater than &nbsp;$10^{\rm -6}$?
 +
|type="{}"}
 +
$N_0/E_{\rm B} \  = \ $ { 1.53 3% } $\ \cdot 10^{\rm -5}$
 +
 
 +
{For the assumptions made in&nbsp; '''(3)''',&nbsp; give a lower  and an upper bound for the&nbsp; "average error probability" &nbsp; $p_{\rm S}$.&nbsp;
 +
|type="{}"}
 +
$p_\text{ S, min}\hspace{0.02cm} \  = \ $ { 0.25 3% } $\ \cdot 10^{\rm -6}$
 +
$p_\text{ S, max} \  = \ $ { 1 3% } $\ \cdot 10^{\rm -6}$
 
</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''  
+
'''(1)'''&nbsp; For the optimization it is sufficient to maximize the quotient&nbsp; $\ddot{o}(T_{\rm D})/\sigma_d$:
'''(2)'''  
+
*This is maximized from the values given in the table for the cutoff frequency &nbsp;$f_{\rm G, opt} \cdot T \underline {= 0.4}$&nbsp; with&nbsp; $0.735/0.197 \approx 3.73$.
'''(3)'''  
+
*As a comparison: &nbsp; For &nbsp;$f_{\rm G} \cdot T = 0.3$&nbsp; the result is&nbsp; $0.192/0.094 \approx 2.04$&nbsp; due to the smaller eye opening.
'''(4)'''  
+
*For &nbsp;$f_{\rm G} \cdot T = 0.5$&nbsp; the quotient is also smaller than for the optimum:&nbsp; $1.159/0.379 \approx 3.05$.
'''(5)'''  
+
*An even larger cutoff frequency leads to a very large noise rms value without simultaneously increasing the vertical eye opening in the same way.
 +
 
 +
 
 +
 
 +
'''(2)'''&nbsp; Using the result from&nbsp; '''(1)''',&nbsp; we further obtain:
 +
:$$\rho_{\rm U} = \left ( {3.73}/{2} \right )^2 \approx 3.48 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}
 +
10 \cdot {\rm
 +
lg}\hspace{0.1cm}\rho_{\rm U} \hspace{0.15cm}\underline { = 5.41\,{\rm dB}}\hspace{0.3cm} \Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q}\left (
 +
{3.73}/{2} \right) \hspace{0.15cm}\underline {\approx 0.031} \hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(3)'''&nbsp; With the given&nbsp; $10 \cdot {\rm lg} \, E_{\rm B}/N_0 = 40 \ \rm dB$,&nbsp; i.e. $E_{\rm B}/N_0 = 10^4$,&nbsp; the worst-case signal-to-noise ratio has been found to be&nbsp; $10 \cdot {\rm lg} \, \rho_{\rm U} \approx 5.41 \, {\rm dB}$.
 +
*However,&nbsp; for the worst-case error probability&nbsp; $p_{\rm U} = 10^{\rm -6}$ &nbsp; &rArr; &nbsp;  $10 \cdot {\rm lg} \, \rho_{\rm U} > 13.55 \, {\rm dB}$&nbsp; must be obtained.
 +
*This is achieved by increasing the quotient&nbsp; $E_{\rm B}/N_0$&nbsp; accordingly:
 +
:$$10 \cdot {\rm
 +
lg}\hspace{0.1cm}{E_{\rm B}}/{N_0} = 40\,{\rm dB}
 +
\hspace{0.1cm}+\hspace{0.1cm}13.55\,{\rm dB}
 +
\hspace{0.1cm}-\hspace{0.1cm}5.41\,{\rm dB}= 48.14\,{\rm dB}\hspace{0.3cm}
 +
\Rightarrow
 +
\hspace{0.3cm} {E_{\rm B}}/{N_0} = 10^{4.814}\approx 65163
 +
\hspace{0.3cm}\Rightarrow \hspace{0.3cm}  {N_0}/{E_{\rm B}}\hspace{0.15cm}\underline {  =
 +
1.53 \cdot 10^{-5}} \hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(4)'''&nbsp;
 +
*The upper bound&nbsp; for $p_{\rm S}$&nbsp; is equal to the worst-case error probability&nbsp; $p_{\rm U} = \underline {10^{\rm -6}}$.
 +
 +
*The lower bound is&nbsp; $\underline {0.25 \cdot 10^{\rm -6}}$,&nbsp; which is smaller by a factor of&nbsp; $4$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
[[Category:Aufgaben zu Digitalsignalübertragung|^3.3 Kanalverzerrungen und Entzerrung^]]
+
[[Category:Digital Signal Transmission: Exercises|^3.3 Channel Distortion and Equalization^]]

Latest revision as of 14:06, 28 June 2022

Normalized system parameters for different cutoff frequencies

We consider a redundancy-free binary transmission system with the following specifications:

  • The transmission pulses are NRZ rectangular and have energy  $E_{\rm B} = s_0^2 \cdot T$.
  • The channel is a coaxial cable with characteristic cable attenuation  $a_* = 40 \, {\rm dB}$.
  • AWGN noise with (one-sided) noise power density  $N_0 = 0.0001 \cdot E_{\rm B}$  is present.
  • The receiver frequency response  $H_{\rm E}(f)$  includes an ideal channel equalizer  $H_{\rm K}^{\rm -1}(f)$  and a Gaussian low-pass filter  $H_{\rm G}(f)$  with cutoff frequency  $f_{\rm G}$  for noise power limitation.


The table shows the eye opening   $\ddot{o}(T_{\rm D})$   as well as the detection noise rms value   $\sigma_{\rm d}$   – each normalized to the transmitted amplitude  $s_0$  – for different cutoff frequencies  $f_{\rm G}$.  The cutoff frequency is to be chosen such that the worst-case error probability is as small as possible,  with the following definition:

$$p_{\rm U} = {\rm Q} \left( \frac{\ddot{o}(T_{\rm D})/2}{ \sigma_d} \right) \hspace{0.3cm}\Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q} \left( \sqrt{\rho_{\rm U}}\right)$$
  • This quantity represents an upper bound for the mean error probability   $p_{\rm S} \le p_{\rm U}$.
  • For  $f_{\rm G} \cdot T ≥ 0.4$,  a lower bound can also be given:   $p_{\rm S} \ge p_{\rm U}/4$.


Notes:



Questions

1

Within the given grid,  determine the optimal cutoff frequency with respect to the  "worst-case error probability"  criterion.

$f_\text{G, opt} \cdot T \ = \ $

2

What values does this give for the  "worst-case signal-to-noise ratio"  and the worst-case error probability?

$f_\text{G} = \text{G, opt:}\hspace{0.4cm} 10 \cdot {\rm lg} \, \rho_{\rm U} \ = \ $

${\ \rm dB}$
$\hspace{4.07cm}p_{\rm U} \ = \ $

$\ \rm \%$

3

To what value would we need to reduce the noise power density  $N_0$  (with respect to signal energy)  so that  $p_{\rm U}$  is not greater than  $10^{\rm -6}$?

$N_0/E_{\rm B} \ = \ $

$\ \cdot 10^{\rm -5}$

4

For the assumptions made in  (3),  give a lower and an upper bound for the  "average error probability"   $p_{\rm S}$. 

$p_\text{ S, min}\hspace{0.02cm} \ = \ $

$\ \cdot 10^{\rm -6}$
$p_\text{ S, max} \ = \ $

$\ \cdot 10^{\rm -6}$


Solution

(1)  For the optimization it is sufficient to maximize the quotient  $\ddot{o}(T_{\rm D})/\sigma_d$:

  • This is maximized from the values given in the table for the cutoff frequency  $f_{\rm G, opt} \cdot T \underline {= 0.4}$  with  $0.735/0.197 \approx 3.73$.
  • As a comparison:   For  $f_{\rm G} \cdot T = 0.3$  the result is  $0.192/0.094 \approx 2.04$  due to the smaller eye opening.
  • For  $f_{\rm G} \cdot T = 0.5$  the quotient is also smaller than for the optimum:  $1.159/0.379 \approx 3.05$.
  • An even larger cutoff frequency leads to a very large noise rms value without simultaneously increasing the vertical eye opening in the same way.


(2)  Using the result from  (1),  we further obtain:

$$\rho_{\rm U} = \left ( {3.73}/{2} \right )^2 \approx 3.48 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm U} \hspace{0.15cm}\underline { = 5.41\,{\rm dB}}\hspace{0.3cm} \Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q}\left ( {3.73}/{2} \right) \hspace{0.15cm}\underline {\approx 0.031} \hspace{0.05cm}.$$


(3)  With the given  $10 \cdot {\rm lg} \, E_{\rm B}/N_0 = 40 \ \rm dB$,  i.e. $E_{\rm B}/N_0 = 10^4$,  the worst-case signal-to-noise ratio has been found to be  $10 \cdot {\rm lg} \, \rho_{\rm U} \approx 5.41 \, {\rm dB}$.

  • However,  for the worst-case error probability  $p_{\rm U} = 10^{\rm -6}$   ⇒   $10 \cdot {\rm lg} \, \rho_{\rm U} > 13.55 \, {\rm dB}$  must be obtained.
  • This is achieved by increasing the quotient  $E_{\rm B}/N_0$  accordingly:
$$10 \cdot {\rm lg}\hspace{0.1cm}{E_{\rm B}}/{N_0} = 40\,{\rm dB} \hspace{0.1cm}+\hspace{0.1cm}13.55\,{\rm dB} \hspace{0.1cm}-\hspace{0.1cm}5.41\,{\rm dB}= 48.14\,{\rm dB}\hspace{0.3cm} \Rightarrow \hspace{0.3cm} {E_{\rm B}}/{N_0} = 10^{4.814}\approx 65163 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} {N_0}/{E_{\rm B}}\hspace{0.15cm}\underline { = 1.53 \cdot 10^{-5}} \hspace{0.05cm}.$$


(4) 

  • The upper bound  for $p_{\rm S}$  is equal to the worst-case error probability  $p_{\rm U} = \underline {10^{\rm -6}}$.
  • The lower bound is  $\underline {0.25 \cdot 10^{\rm -6}}$,  which is smaller by a factor of  $4$.