Difference between revisions of "Aufgaben:Exercise 3.6: Transversal Filter of the Optimal Nyquist Equalizer"

From LNTwww
 
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''  The input pulse $g_x(t)$ is given by the following samples at multiples of $T$:
+
'''(1)'''  The input pulse  $g_x(t)$  is given by the following samples at multiples of  $T$:
 
:$$g_x(t = 0) = 1,\hspace{0.2cm}g_x(t = \pm T) =
 
:$$g_x(t = 0) = 1,\hspace{0.2cm}g_x(t = \pm T) =
 
0.5,\hspace{0.2cm}g_x(t = \pm 2 T) = ... = 0
 
0.5,\hspace{0.2cm}g_x(t = \pm 2 T) = ... = 0
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
*Thus, the following system of equations can be set up:
+
*Thus,  the following system of equations can be set up:
 +
[[File:P_ID1433__Dig_A_3_6_b.png|right|frame|Output pulse for  $N = 1$]]
 
:$$t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} k_0 \cdot 1.0 + k_1 \cdot 2
 
:$$t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} k_0 \cdot 1.0 + k_1 \cdot 2
 
\cdot  0.5 = 1\hspace{0.05cm},$$
 
\cdot  0.5 = 1\hspace{0.05cm},$$
 
:$$t = T\hspace{-0.1cm}:\hspace{0.2cm}g_1 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} k_0 \cdot 0.5 + k_1 \cdot 1.0 = 0
 
:$$t = T\hspace{-0.1cm}:\hspace{0.2cm}g_1 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} k_0 \cdot 0.5 + k_1 \cdot 1.0 = 0
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
[[File:P_ID1433__Dig_A_3_6_b.png|right|frame|Output pulse for  $N = 1$]]
+
*From these equations,  it follows that  $k_0 \ \underline {= \ 2}$  and  $k_1 \ \underline {= \ –1}$.
*From these equations, it follows that $k_0 \ \underline {= \ 2}$ and $k_1 \ \underline {= \ –1}$.
 
  
  
  
'''(2)'''  The values $g_0 = 1$  and $g_1 = 0$  have already been used as a basis for the optimization and are therefore undisputed.
+
'''(2)'''  The values  $g_0 = 1$  and  $g_1 = 0$  have already been used as a basis for the optimization and are therefore undisputed.
*At time $t = 2T$, the output results, where $k_{-1} = k_1 = -1$:
+
*At time  $t = 2T$,  the output results,  where $k_{-1} = k_1 = -1$:
 
:$$g_2 = g_y(t =  2 T) = g_x(t =  T) \cdot k_{-1}\hspace{0.15cm}\underline { = -0.5 =
 
:$$g_2 = g_y(t =  2 T) = g_x(t =  T) \cdot k_{-1}\hspace{0.15cm}\underline { = -0.5 =
 
g_{-2}} \hspace{0.05cm}.$$
 
g_{-2}} \hspace{0.05cm}.$$
*Since all input values are zero at times $2T$, $3T$ and $4T$, $g_3 = g_y(t = 3T) \underline {= \ 0}$.  
+
*Since all input values are zero at times  $2T$,  $3T$  and  $4T$   ⇒   $g_3 = g_y(t = 3T) \underline {= \ 0}$.  
*This gives the output pulse $g_y(t)$ as shown in the sketch.
+
*This gives the output pulse  $g_y(t)$ as  shown in the sketch.
  
  
[[File:P_ID1439__Dig_A_3_6_d.png|right|frame|Output pulse for  $N = 2$]]
 
 
'''(3)'''  For a second order filter, the system of equations is:
 
'''(3)'''  For a second order filter, the system of equations is:
 
:$$t = 2T\hspace{-0.1cm}:\hspace{0.2cm}g_2 = k_1 \cdot 0.5 + k_2 \cdot 1.0 = 0 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} k_2 = - 0.5 \cdot k_1\hspace{0.05cm},$$
 
:$$t = 2T\hspace{-0.1cm}:\hspace{0.2cm}g_2 = k_1 \cdot 0.5 + k_2 \cdot 1.0 = 0 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} k_2 = - 0.5 \cdot k_1\hspace{0.05cm},$$
 +
[[File:P_ID1439__Dig_A_3_6_d.png|right|frame|Output pulse for  $N = 2$]]
 
:$$t = T\hspace{-0.1cm}:\hspace{0.2cm}g_1= k_0 \cdot 0.5 +k_1 \cdot 1.0 + k_2 \cdot 0.5 = 0\hspace{0.05cm},$$
 
:$$t = T\hspace{-0.1cm}:\hspace{0.2cm}g_1= k_0 \cdot 0.5 +k_1 \cdot 1.0 + k_2 \cdot 0.5 = 0\hspace{0.05cm},$$
 
:$$\hspace{1.6cm}\Rightarrow \hspace{0.3cm}
 
:$$\hspace{1.6cm}\Rightarrow \hspace{0.3cm}
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:$$t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0 = k_0 \cdot 1.0 + k_1 \cdot 0.5 + k_1 \cdot 0.5 = 1\hspace{0.05cm},$$
 
:$$t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0 = k_0 \cdot 1.0 + k_1 \cdot 0.5 + k_1 \cdot 0.5 = 1\hspace{0.05cm},$$
 
:$$\hspace{1.6cm}\Rightarrow \hspace{0.3cm} k_0 = 3 \hspace{0.05cm}.$$
 
:$$\hspace{1.6cm}\Rightarrow \hspace{0.3cm} k_0 = 3 \hspace{0.05cm}.$$
*Thus, the optimal coefficients are
+
*Thus,  the optimal coefficients are
 
:$$k_0 \ \underline {=  \ 3},k_1 \ \underline {= \ –2},  k_2 \ \underline {=  \ 1}.$$
 
:$$k_0 \ \underline {=  \ 3},k_1 \ \underline {= \ –2},  k_2 \ \underline {=  \ 1}.$$
  
  
'''(4)'''  Proceeding in the same way as in subtask '''(2)''', we obtain  $g_4 \ \underline {= \ 0}$  as well as
+
'''(4)'''  Proceeding in the same way as in subtask  '''(2)''',  we obtain  $g_4 \ \underline {= \ 0}$  as well as
 
:$$g_3 = g_y(t =  3 T) = g_x(t =  T) \cdot k_{-2} = 0.5 \cdot 1
 
:$$g_3 = g_y(t =  3 T) = g_x(t =  T) \cdot k_{-2} = 0.5 \cdot 1
 
\hspace{0.15cm}\underline {= 0.5} \hspace{0.05cm}.$$
 
\hspace{0.15cm}\underline {= 0.5} \hspace{0.05cm}.$$
  
*However, the two graphs also show that for the triangular shape here, the optimal Nyquist equalization does not improve anything.
+
*However,  the two graphs also show that for the triangular shape here,  the optimal Nyquist equalization does not improve anything.  The eye is  "just closed"  in all cases:
*The eye is just closed in all cases:
 
 
:$$N = 0\hspace{-0.1cm}:\hspace{0.2cm}  \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} g_0 - 2 \cdot g_1 = 1- 2 \cdot 0.5 = 0  \hspace{0.05cm}, $$
 
:$$N = 0\hspace{-0.1cm}:\hspace{0.2cm}  \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} g_0 - 2 \cdot g_1 = 1- 2 \cdot 0.5 = 0  \hspace{0.05cm}, $$
 
:$$N = 1\hspace{-0.1cm}:\hspace{0.2cm}  \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  g_0 - 2 \cdot |g_2 | = 1- 2 \cdot 0.5 = 0  \hspace{0.05cm}, $$
 
:$$N = 1\hspace{-0.1cm}:\hspace{0.2cm}  \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  g_0 - 2 \cdot |g_2 | = 1- 2 \cdot 0.5 = 0  \hspace{0.05cm}, $$

Latest revision as of 16:41, 22 June 2022

Transversal filter of the
Optimal Nyquist Equalizer

At the input of the symmetric second order transversal filter  $(N = 2)$  shown in the diagram there is a triangular pulse  $($normalized to $1)$:

$$g_x(t) = \left\{ \begin{array}{c} 1 - {|\hspace{0.05cm}t\hspace{0.05cm}|}/{(2T)} \\ \\ 0 \\ \end{array} \right. \begin{array}{*{1}c} {\rm{for}}\\ \\ {\rm{for}} \\ \end{array} \begin{array}{*{20}c}|\hspace{0.05cm}t\hspace{0.05cm}| \le 2\hspace{0.05cm}T, \\ \\ |\hspace{0.05cm}t\hspace{0.05cm}| \ge 2\hspace{0.05cm}T. \\ \end{array}$$

If all filter coefficients  $k_0$,  $k_1$  and  $k_2$  are nonzero,  then the following holds for the pulse at the output:

$$g_y(t) \ = k_0 \cdot g_x(t) + k_1 \cdot \big[ g_x(t-T)+ g_x(t+T) \big] + k_2 \cdot \big[ g_x(t-2T)+ g_x(t+2T) \big]\hspace{0.05cm}.$$

By appropriate choice of filter coefficients  $k_0$,  $k_1$  and  $k_2$,  the output pulse can satisfy the following conditions:

$$g_0 = g_y(t = 0) = 1,\hspace{0.2cm}g_1 = g_y(t = \pm T) = 0,\hspace{0.2cm}g_2 = g_y(t = \pm 2 T) = 0 \hspace{0.05cm}.$$
  • A first order filter  $(N = 1)$  is obtained from the above arrangement and equation by setting the coefficient  $k_2 = 0$. 
  • Then,  by appropriate choice of  $k_0$  and  $k_1$,   $g_0 = 1$  and  $g_1 = 0$  can be obtained. However,  in this case,  always will be  $g_2 ≠ 0$. 



Note:  The exercise belongs to the chapter  "Linear Nyquist Equalization".


Questions

1

What are the optimal coefficients for the first order filter   ⇒   $k_2 = 0$?

$k_0\ = \ $

$k_1\ = \ $

2

What are the output values at time points  $t = 2T$  and  $t = 3T$?

$g_2\ = \ $

$g_3\ = \ $

3

What are the optimal coefficients for the second order filter  $(N = 2)$?

$k_0\ = \ $

$k_1\ = \ $

$k_2\ = \ $

4

What are the output values at time points  $t = 3T$  and  $t = 4T$?

$g_3\ = \ $

$g_4\ = \ $


Solution

(1)  The input pulse  $g_x(t)$  is given by the following samples at multiples of  $T$:

$$g_x(t = 0) = 1,\hspace{0.2cm}g_x(t = \pm T) = 0.5,\hspace{0.2cm}g_x(t = \pm 2 T) = ... = 0 \hspace{0.05cm}.$$
  • Thus,  the following system of equations can be set up:
Output pulse for  $N = 1$
$$t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} k_0 \cdot 1.0 + k_1 \cdot 2 \cdot 0.5 = 1\hspace{0.05cm},$$
$$t = T\hspace{-0.1cm}:\hspace{0.2cm}g_1 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} k_0 \cdot 0.5 + k_1 \cdot 1.0 = 0 \hspace{0.05cm}.$$
  • From these equations,  it follows that  $k_0 \ \underline {= \ 2}$  and  $k_1 \ \underline {= \ –1}$.


(2)  The values  $g_0 = 1$  and  $g_1 = 0$  have already been used as a basis for the optimization and are therefore undisputed.

  • At time  $t = 2T$,  the output results,  where $k_{-1} = k_1 = -1$:
$$g_2 = g_y(t = 2 T) = g_x(t = T) \cdot k_{-1}\hspace{0.15cm}\underline { = -0.5 = g_{-2}} \hspace{0.05cm}.$$
  • Since all input values are zero at times  $2T$,  $3T$  and  $4T$   ⇒   $g_3 = g_y(t = 3T) \underline {= \ 0}$.
  • This gives the output pulse  $g_y(t)$ as  shown in the sketch.


(3)  For a second order filter, the system of equations is:

$$t = 2T\hspace{-0.1cm}:\hspace{0.2cm}g_2 = k_1 \cdot 0.5 + k_2 \cdot 1.0 = 0 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} k_2 = - 0.5 \cdot k_1\hspace{0.05cm},$$
Output pulse for  $N = 2$
$$t = T\hspace{-0.1cm}:\hspace{0.2cm}g_1= k_0 \cdot 0.5 +k_1 \cdot 1.0 + k_2 \cdot 0.5 = 0\hspace{0.05cm},$$
$$\hspace{1.6cm}\Rightarrow \hspace{0.3cm} k_1 = - {2}/{3} \cdot k_0\hspace{0.05cm},$$
$$t = 0\hspace{-0.1cm}:\hspace{0.2cm}g_0 = k_0 \cdot 1.0 + k_1 \cdot 0.5 + k_1 \cdot 0.5 = 1\hspace{0.05cm},$$
$$\hspace{1.6cm}\Rightarrow \hspace{0.3cm} k_0 = 3 \hspace{0.05cm}.$$
  • Thus,  the optimal coefficients are
$$k_0 \ \underline {= \ 3},k_1 \ \underline {= \ –2}, k_2 \ \underline {= \ 1}.$$


(4)  Proceeding in the same way as in subtask  (2),  we obtain  $g_4 \ \underline {= \ 0}$  as well as

$$g_3 = g_y(t = 3 T) = g_x(t = T) \cdot k_{-2} = 0.5 \cdot 1 \hspace{0.15cm}\underline {= 0.5} \hspace{0.05cm}.$$
  • However,  the two graphs also show that for the triangular shape here,  the optimal Nyquist equalization does not improve anything.  The eye is  "just closed"  in all cases:
$$N = 0\hspace{-0.1cm}:\hspace{0.2cm} \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} g_0 - 2 \cdot g_1 = 1- 2 \cdot 0.5 = 0 \hspace{0.05cm}, $$
$$N = 1\hspace{-0.1cm}:\hspace{0.2cm} \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} g_0 - 2 \cdot |g_2 | = 1- 2 \cdot 0.5 = 0 \hspace{0.05cm}, $$
$$N = 2\hspace{-0.1cm}:\hspace{0.2cm} \ddot{o}/2 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} g_0 - 2 \cdot g_3 = 1- 2 \cdot 0.5 = 0 \hspace{0.05cm}.$$