Difference between revisions of "Aufgaben:Exercise 3.11: Viterbi Receiver and Trellis Diagram"

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{{quiz-Header|Buchseite=Digital_Signal_Transmission/Viterbi_Receiver}}
 
{{quiz-Header|Buchseite=Digital_Signal_Transmission/Viterbi_Receiver}}
  
[[File:P_ID1475__Dig_A_3_11.png|right|frame|Trellis diagram for a precursor]]
+
[[File:P_ID1475__Dig_A_3_11.png|right|frame|Trellis diagram <br>for one precursor]]
The Viterbi receiver allows a low-effort realization of the maximum likelihood decision rule. It contains the system components listed below:
+
The Viterbi receiver allows a low-effort realization of the maximum likelihood decision rule.&nbsp; It contains the system components listed below:
* a matched filter adapted to the basic transmission pulse with frequency response &nbsp;$H_{\rm MF}(f)$&nbsp; and output signal &nbsp; $m(t)$,
+
* A matched filter adapted to the basic transmission pulse with frequency response &nbsp;$H_{\rm MF}(f)$&nbsp; and output signal &nbsp; $m(t)$,
* a sampler spaced at the symbol duration (bit duration)&nbsp; $T$, which converts the continuous-time signal &nbsp; $m(t)$&nbsp; into the discrete-time sequence &nbsp; $&#9001;m_{\rm \nu}&#9002;$,&nbsp;
 
* a decorrelation filter with frequency response &nbsp; $H_{\rm DF}(f)$&nbsp; for removing statistical ties between the noise components of the sequence &nbsp; $&#9001;d_{\rm \nu}&#9002;$,
 
* the Viterbi decision, which uses a trellis-based algorithm to obtain the sink symbol sequence&nbsp; $&#9001;v_{\rm \nu}&#9002;$.&nbsp;
 
  
 +
* a sampler spaced at the symbol duration&nbsp; $T$,&nbsp; which converts the continuous-time signal &nbsp; $m(t)$&nbsp; into the discrete-time sequence &nbsp; $&#9001;m_{\rm \nu}&#9002;$,&nbsp;
 +
 +
* a decorrelation filter with frequency response &nbsp; $H_{\rm DF}(f)$&nbsp; for removing statistical ties between noise components of the sequence &nbsp; $&#9001;d_{\rm \nu}&#9002;$,
  
The graph shows the simplified trellis diagram of the two states "$0$" and "$1$" for time points &nbsp; $\nu &#8804; 5$. This diagram is obtained as a result of evaluating the two minimum total error quantities &nbsp; ${\it \Gamma}_{\rm \nu}(0)$&nbsp; and&nbsp; ${\it \Gamma}_{\rm \nu}(1)$&nbsp; corresponding to &nbsp; [[Aufgaben:Exercise_3.11Z:_Maximum_Likelihood_Error_Variables|"Exercise 3.11Z"]].
+
* the Viterbi decision,&nbsp; which uses a trellis-based algorithm to obtain the sink symbol sequence&nbsp; $&#9001;v_{\rm \nu}&#9002;$.&nbsp;  
  
  
 +
The graph shows the simplified trellis diagram of the two states&nbsp; "$0$"&nbsp; and&nbsp; "$1$"&nbsp; for time points &nbsp; $\nu &#8804; 5$.&nbsp; This diagram is obtained as a result of evaluating the two minimum accumulated metrics &nbsp; ${\it \Gamma}_{\rm \nu}(0)$&nbsp; and&nbsp; ${\it \Gamma}_{\rm \nu}(1)$&nbsp; corresponding to &nbsp; [[Aufgaben:Exercise_3.11Z:_Maximum_Likelihood_Error_Variables|Exercise 3.11Z]].
  
  
  
  
''Notes:''
+
Notes:  
*The exercise belongs to the chapter &nbsp;  [[Digital_Signal_Transmission/Viterbi_Receiver|"Viterbi Receiver"]].
+
*The exercise belongs to the chapter&nbsp;  [[Digital_Signal_Transmission/Viterbi_Receiver|"Viterbi Receiver"]].
*Reference is also made to the section&nbsp; [[Digital_Signal_Transmission/Optimal_Receiver_Strategies#MAP_and_Maximum.E2.80.93Likelihood_decision_rule|"MAP and Maximum–Likelihood decision rule"]].
+
 
 +
*Reference is also made to the section&nbsp; [[Digital_Signal_Transmission/Optimal_Receiver_Strategies#Maximum-a-posteriori_and_maximum.E2.80.93likelihood_decision_rule|"Maximum-a-posteriori and Maximum–Likelihood decision rule"]].
 
   
 
   
* All quantities here are to be understood normalized. Also assume unipolar and equal probability amplitude coefficients: &nbsp;${\rm Pr} (a_\nu = 0) = {\rm Pr} (a_\nu = 1)= 0.5.$
+
* All quantities here are to be understood normalized. Also assume unipolar and equal probability amplitude coefficients: &nbsp;
* The topic is also covered in the interactive applet&nbsp;  [[Applets:Viterbi|"Properties of the Viterbi Receiver"]].
+
:$${\rm Pr} (a_\nu = 0) = {\rm Pr} (a_\nu = 1)= 0.5.$$
  
  
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+ The matched filter &nbsp;$H_{\rm MF}(f)$&nbsp; is mainly used for noise power limitation.
 
+ The matched filter &nbsp;$H_{\rm MF}(f)$&nbsp; is mainly used for noise power limitation.
 
+ The decorrelation filter removes ties between samples.
 
+ The decorrelation filter removes ties between samples.
- The noise power is only affected by &nbsp;$H_{\rm MF}(f)$, not by &nbsp;$H_{\rm DF}(f)$.&nbsp;  
+
- The noise power is only affected by &nbsp;$H_{\rm MF}(f)$,&nbsp; not by &nbsp;$H_{\rm DF}(f)$.&nbsp;  
  
 
{At what times &nbsp;$\nu$&nbsp; can we finally decide the current symbol &nbsp;$a_{\rm \nu}$?&nbsp;  
 
{At what times &nbsp;$\nu$&nbsp; can we finally decide the current symbol &nbsp;$a_{\rm \nu}$?&nbsp;  
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+ $\nu = 5.$
 
+ $\nu = 5.$
  
{What is the sequence decided by the Viterbi receiver?
+
{What is the total sequence decided by the Viterbi receiver?
 
|type="{}"}
 
|type="{}"}
 
$a_1 \ = \ $ { 0. }
 
$a_1 \ = \ $ { 0. }
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; The <u>first two solutions</u> are correct:  
+
'''(1)'''&nbsp; The&nbsp; <u>first two solutions</u>&nbsp; are correct:  
*The signal $m(t)$ after the matched filter $H_{\rm MF}(f)$ has the largest possible signal-to-interference power ratio.
+
*The signal&nbsp; $m(t)$&nbsp; after the matched filter&nbsp; $H_{\rm MF}(f)$&nbsp; has the largest possible signal-to-interference power ratio&nbsp; $\rm (SNR)$.
* However, the noise components of the sequence $&#9001;m_{\rm \nu}&#9002;$ are (strongly) correlated due to the spectral shaping.
+
* However,&nbsp; the noise components of the sequence&nbsp; $&#9001;m_{\rm \nu}&#9002;$&nbsp; are (strongly) correlated due to the spectral shaping.
*The task of the discrete-time decorrelation filter with the frequency response $H_{\rm DF}(f)$ is to dissolve these bonds, which is why the name "whitening filter" is also used for $H_{\rm DF}(f)$.   
+
*The task of the discrete-time decorrelation filter with the frequency response&nbsp; $H_{\rm DF}(f)$&nbsp; is to dissolve these bindings,&nbsp; which is why the name&nbsp; "whitening filter"&nbsp; is also used for&nbsp; $H_{\rm DF}(f)$.   
*However, this is possible only at the cost of increased noise power &nbsp; &#8658; &nbsp; consequently, the last proposed solution does not apply.
+
*However,&nbsp; this is possible only at the cost of increased noise power &nbsp; &#8658; &nbsp; consequently,&nbsp; the last proposed solution does not apply.
 
 
  
  
'''(2)'''&nbsp; The two arrows arriving at $\underline {\nu = 1}$ are each drawn in blue and indicate the symbol $a_1 = 0$. Thus, the initial symbol $a_1$ is already fixed at this point. Similarly, the symbols $a_3 = 1$ and $a_5 = 0$ are already fixed at the timesn $\underline {\nu = 3}$ and $\underline {\nu = 5}$, respectively.
 
  
In contrast, at time $\nu = 2$, a decision regarding symbol $a_2$ is not possible.
+
'''(2)'''&nbsp; The two arrows arriving at &nbsp; $\underline {\nu = 1}$&nbsp; are each drawn in blue and indicate the symbol&nbsp; $a_1 = 0$.&nbsp; Thus,&nbsp; the initial symbol&nbsp; $a_1$&nbsp; is already fixed at this point.&nbsp; Similarly,&nbsp; the symbols&nbsp; $a_3 = 1$&nbsp; and&nbsp; $a_5 = 0$&nbsp; are already fixed at times&nbsp; $\underline {\nu = 3}$&nbsp; and&nbsp; $\underline {\nu = 5}$,&nbsp; respectively.
*Under the hypothesis that the following symbol $a_3 = 0$ would result in symbol $a_2 = 1$ (at "$0$" a red path arrives, thus coming from "$1$").  
 
* In contrast, the hypothesis $a_3 = 1$ leads to the result $a_2 = 0$ (the path arriving at "$1$" is blue).
 
  
 +
In contrast,&nbsp; at time $\nu = 2$,&nbsp; a decision regarding symbol&nbsp; $a_2$&nbsp; is not possible.
 +
*Under the hypothesis that the following symbol&nbsp; $a_3 = 0$&nbsp; would result in symbol&nbsp; $a_2 = 1$&nbsp; $($at&nbsp; "$0$"&nbsp; a red path arrives,&nbsp; thus coming from&nbsp; "$1$"$)$.
 +
* In contrast,&nbsp; the hypothesis&nbsp; $a_3 = 1$&nbsp; leads to the result&nbsp; $a_2 = 0$&nbsp; $($the path arriving at&nbsp; "$1$"&nbsp; is blue$)$.
  
The situation is similar at time $\nu = 4$.
+
The situation is similar at time&nbsp; $\nu = 4$.
  
  
'''(3)'''&nbsp; From the continuous paths at $\nu = 5$ it can be seen:
+
'''(3)'''&nbsp; From the continuous paths at&nbsp; $\nu = 5$&nbsp; it can be seen:
 
:$$a_{1}\hspace{0.15cm}\underline {=0} \hspace{0.05cm},\hspace{0.2cm}
 
:$$a_{1}\hspace{0.15cm}\underline {=0} \hspace{0.05cm},\hspace{0.2cm}
 
a_{2}\hspace{0.15cm}\underline { =0} \hspace{0.05cm},\hspace{0.2cm}a_{3}\hspace{0.15cm}\underline {=1}
 
a_{2}\hspace{0.15cm}\underline { =0} \hspace{0.05cm},\hspace{0.2cm}a_{3}\hspace{0.15cm}\underline {=1}
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'''(4)'''&nbsp; Only the <u>second statement</u> is correct:  
+
'''(4)'''&nbsp; Only the&nbsp; <u>second statement</u>&nbsp; is correct:  
*Since the source symbols "$0$" and "$1$" were assumed to be equally probable, the ML receiver (Viterbi) is identical to the MAP receiver.
+
*Since the source symbols&nbsp; "$0$"&nbsp; and&nbsp; "$1$"&nbsp; were assumed to be equally probable,&nbsp; the ML receiver&nbsp; (Viterbi)&nbsp; is identical to the MAP receiver.
*A threshold decision (which makes a symbol-by-symbol decision at each clock) has the same error probability as the Viterbi receiver only if there is no intersymbol interference.
+
*A threshold decision&nbsp; $($which makes a symbol-by-symbol decision at each clock$)$&nbsp; has the same BER as the Viterbi receiver only if there is no intersymbol interference.
*This is obviously not the case here, otherwise it should be possible to make a final decision at every time $\nu$.  
+
*This is obviously not the case here,&nbsp; otherwise it should be possible to make a final decision at every time&nbsp; $\nu$.  
*The first statement is also not true. Indeed, this would mean that the Viterbi receiver can have error probability $0$ in the presence of statistical noise. This is not possible for information-theoretic reasons.
+
*The first statement is also false.&nbsp; Indeed,&nbsp; this would mean that the Viterbi receiver can have error probability&nbsp; $0$&nbsp; in the presence of AWGN noise.&nbsp; <br>This is not possible for information-theoretic reasons.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  

Latest revision as of 14:00, 5 July 2022

Trellis diagram
for one precursor

The Viterbi receiver allows a low-effort realization of the maximum likelihood decision rule.  It contains the system components listed below:

  • A matched filter adapted to the basic transmission pulse with frequency response  $H_{\rm MF}(f)$  and output signal   $m(t)$,
  • a sampler spaced at the symbol duration  $T$,  which converts the continuous-time signal   $m(t)$  into the discrete-time sequence   $〈m_{\rm \nu}〉$, 
  • a decorrelation filter with frequency response   $H_{\rm DF}(f)$  for removing statistical ties between noise components of the sequence   $〈d_{\rm \nu}〉$,
  • the Viterbi decision,  which uses a trellis-based algorithm to obtain the sink symbol sequence  $〈v_{\rm \nu}〉$. 


The graph shows the simplified trellis diagram of the two states  "$0$"  and  "$1$"  for time points   $\nu ≤ 5$.  This diagram is obtained as a result of evaluating the two minimum accumulated metrics   ${\it \Gamma}_{\rm \nu}(0)$  and  ${\it \Gamma}_{\rm \nu}(1)$  corresponding to   Exercise 3.11Z.



Notes:

  • All quantities here are to be understood normalized. Also assume unipolar and equal probability amplitude coefficients:  
$${\rm Pr} (a_\nu = 0) = {\rm Pr} (a_\nu = 1)= 0.5.$$


Questions

1

Which of the following statements are true?

The matched filter  $H_{\rm MF}(f)$  is mainly used for noise power limitation.
The decorrelation filter removes ties between samples.
The noise power is only affected by  $H_{\rm MF}(f)$,  not by  $H_{\rm DF}(f)$. 

2

At what times  $\nu$  can we finally decide the current symbol  $a_{\rm \nu}$? 

$\nu = 1,$
$\nu = 2,$
$\nu = 3,$
$\nu = 4,$
$\nu = 5.$

3

What is the total sequence decided by the Viterbi receiver?

$a_1 \ = \ $

$a_2 \ = \ $

$a_3 \ = \ $

$a_4 \ = \ $

$a_5 \ = \ $

4

Which of the following statements are true?

It is certain that the detected sequence was also sent.
A MAP receiver would have the same error probability.
Threshold decision is the same as this maximum likelihood receiver.


Solution

(1)  The  first two solutions  are correct:

  • The signal  $m(t)$  after the matched filter  $H_{\rm MF}(f)$  has the largest possible signal-to-interference power ratio  $\rm (SNR)$.
  • However,  the noise components of the sequence  $〈m_{\rm \nu}〉$  are (strongly) correlated due to the spectral shaping.
  • The task of the discrete-time decorrelation filter with the frequency response  $H_{\rm DF}(f)$  is to dissolve these bindings,  which is why the name  "whitening filter"  is also used for  $H_{\rm DF}(f)$.
  • However,  this is possible only at the cost of increased noise power   ⇒   consequently,  the last proposed solution does not apply.


(2)  The two arrows arriving at   $\underline {\nu = 1}$  are each drawn in blue and indicate the symbol  $a_1 = 0$.  Thus,  the initial symbol  $a_1$  is already fixed at this point.  Similarly,  the symbols  $a_3 = 1$  and  $a_5 = 0$  are already fixed at times  $\underline {\nu = 3}$  and  $\underline {\nu = 5}$,  respectively.

In contrast,  at time $\nu = 2$,  a decision regarding symbol  $a_2$  is not possible.

  • Under the hypothesis that the following symbol  $a_3 = 0$  would result in symbol  $a_2 = 1$  $($at  "$0$"  a red path arrives,  thus coming from  "$1$"$)$.
  • In contrast,  the hypothesis  $a_3 = 1$  leads to the result  $a_2 = 0$  $($the path arriving at  "$1$"  is blue$)$.

The situation is similar at time  $\nu = 4$.


(3)  From the continuous paths at  $\nu = 5$  it can be seen:

$$a_{1}\hspace{0.15cm}\underline {=0} \hspace{0.05cm},\hspace{0.2cm} a_{2}\hspace{0.15cm}\underline { =0} \hspace{0.05cm},\hspace{0.2cm}a_{3}\hspace{0.15cm}\underline {=1} \hspace{0.05cm},\hspace{0.2cm} a_{4}\hspace{0.15cm}\underline {=0} \hspace{0.05cm},\hspace{0.2cm} a_{5}\hspace{0.15cm}\underline {=0} \hspace{0.05cm}.$$


(4)  Only the  second statement  is correct:

  • Since the source symbols  "$0$"  and  "$1$"  were assumed to be equally probable,  the ML receiver  (Viterbi)  is identical to the MAP receiver.
  • A threshold decision  $($which makes a symbol-by-symbol decision at each clock$)$  has the same BER as the Viterbi receiver only if there is no intersymbol interference.
  • This is obviously not the case here,  otherwise it should be possible to make a final decision at every time  $\nu$.
  • The first statement is also false.  Indeed,  this would mean that the Viterbi receiver can have error probability  $0$  in the presence of AWGN noise. 
    This is not possible for information-theoretic reasons.