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

From LNTwww
Line 2: Line 2:
 
{{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 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 "$0$" 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 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:
 +
*The exercise belongs to the chapter&nbsp;  [[Digital_Signal_Transmission/Viterbi_Receiver|"Viterbi Receiver"]].
  
''Notes:''
 
*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#MAP_and_Maximum.E2.80.93Likelihood_decision_rule|"MAP 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"]].
+
:$${\rm Pr} (a_\nu = 0) = {\rm Pr} (a_\nu = 1)= 0.5.$$
 +
* The topic is also covered with the interactive SWF applet&nbsp;  [[Applets:Viterbi|"Properties of the Viterbi Receiver"]].
  
  
Line 31: Line 34:
 
+ 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;  
Line 41: Line 44:
 
+ $\nu = 5.$
 
+ $\nu = 5.$
  
{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. }

Revision as of 14:13, 4 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.
  • 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 bonds, 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 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.

  • 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 error probability 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 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.