Difference between revisions of "Aufgaben:Exercise 4.13: Four-level QAM"

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{{quiz-Header|Buchseite=Digitalsignalübertragung/Trägerfrequenzsysteme mit kohärenter Demodulation}}
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{{quiz-Header|Buchseite=Digital_Signal_Transmission/Carrier_Frequency_Systems_with_Coherent_Demodulation}}
  
[[File:P_ID2066__Dig_A_4_13.png|right|frame|Signalraumkonstellation der 4–QAM]]
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[[File:P_ID2066__Dig_A_4_13.png|right|frame|Signal space constellation  "4–QAM"]]
Wir betrachten nun eine Quadraturamplitudenmodulation mit $M = 4$ Symbolen und den (normierten) Signalraumpunkten
+
We now consider a quadrature amplitude modulation with  $M = 4$  symbols and the  (normalized)  signal space points
:$$\boldsymbol{ s}_{\rm A} = (+1, +1)\hspace{0.05cm},\hspace{0.2cm}\boldsymbol{ s}_{\rm B} = (-1, +1)\hspace{0.05cm},$$
+
:$$\boldsymbol{ s}_{\rm A} = (+1, +1)\hspace{0.05cm},\hspace{0.2cm}\boldsymbol{ s}_{\rm B} = (-1, +1)\hspace{0.05cm},\hspace{0.2cm} \boldsymbol{ s}_{\rm C} = (-1, -1)\hspace{0.05cm},\hspace{0.2cm}\boldsymbol{ s}_{\rm D} = (+1, -1)
:$$ \boldsymbol{ s}_{\rm C} = (-1, -1)\hspace{0.05cm},\hspace{0.2cm}\boldsymbol{ s}_{\rm D} = (+1, -1)
 
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Die Symbole sind gleichwahrscheinlich. Damit kann man zur Berechnung der mittleren Symbolfehlerwahrscheinlichkeit auf die Mittelung verzichten.
+
The symbols are equally probable.  Thus,  averaging can be omitted to calculate the average symbol error probability.
  
Beispielsweise gilt:
+
For example:
:$$p_{\rm S} = {\rm Pr}({\cal{E}}) = {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm entschieden} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm gesendet})
+
:$$p_{\rm S} = {\rm Pr}({\cal{E}}) = {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted})
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Die Zuordnung der Symbole zu <i>Bitdupeln</i> kann ebenfalls der Grafik (rote Beschriftungen) entnommen werden. Hierbei ist die Graycodierung vorausgesetzt.
+
The assignment of the symbols to&nbsp; "bit-duples"&nbsp; can also be taken from the graphic&nbsp; (red labels).&nbsp; Gray coding is assumed here.
  
''Hinweise:''
+
 
* Die Aufgabe bezieht sich auf die [[Digitalsignal%C3%BCbertragung/Tr%C3%A4gerfrequenzsysteme_mit_koh%C3%A4renter_Demodulation#Quadraturamplitudenmodulation_.28M.E2.80.93QAM.29| Theorieseite 6]] von Kapitel 4.4.  
+
 
* Für die Teilaufgabe (4) ist der (zeitdiskrete) AWGN&ndash;Kanal mit der Varianz $\sigma_n^2 = N_0/2$ vorausgesetzt.  
+
 
* Für die Wahrscheinlichkeit, dass durch dessen Rauschsignal $n$ ein Symbol horizontal oder vertikal verfälscht wird, gilt mit der komplementären Gaußschen Fehlerfunktion:
+
 
 +
 
 +
Notes:
 +
* The exercise belongs to the chapter&nbsp; [[Digital_Signal_Transmission/Carrier_Frequency_Systems_with_Coherent_Demodulation|"Carrier Frequency Systems with Coherent Demodulation"]].
 +
 +
* Reference is made in particular to the section&nbsp;  [[Digital_Signal_Transmission/Carrier_Frequency_Systems_with_Coherent_Demodulation#Quadrature_amplitude_modulation_.28M-QAM.29|"Quadrature amplitude modulation"]]&nbsp; $\rm (QAM)$.
 +
 +
* For subtask&nbsp; '''(4)''',&nbsp; the (discrete-time) AWGN channel with variance&nbsp; $\sigma_n^2 = N_0/2$&nbsp; is assumed.
 +
 
 +
* For the probability that a symbol is falsified horizontally or vertically by the noise signal&nbsp; $n$,&nbsp; with the complementary Gaussian error function &nbsp;$\rm Q(x)$ holds:
 
:$$p = {\rm Pr}( n < -x_0) = {\rm Pr}( n > + x_0) = {\rm Q}(x_0 / \sigma_n)  
 
:$$p = {\rm Pr}( n < -x_0) = {\rm Pr}( n > + x_0) = {\rm Q}(x_0 / \sigma_n)  
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
* Sollte die Eingabe des Zahlenwertes „0” erforderlich sein, so geben Sie bitte „0.” ein.
+
  
  
  
===Fragebogen===
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===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{Geben Sie als obere Schranke für die Symbolfehlerwahrscheinlichkeit $p_{\rm S}$ die &bdquo;Union Bound&rdquo; an ($p_{\rm UB} &#8805; p_{\rm S}$). Es gelte $p = 0.1$.
+
{Give the&nbsp; "Union Bound"&nbsp; as the upper bound for the symbol error probability&nbsp; $p_{\rm S}$ &nbsp; $(p_{\rm UB} &#8805; p_{\rm S})$.&nbsp; Let&nbsp; $p = 0.1$.
 
|type="{}"}
 
|type="{}"}
$p_{\rm UB}$ = { 0.2 3% }  
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$p_{\rm UB}\ = \ $ { 0.2 3% }  
  
{Wie groß ist die tatsächliche Symbolfehlerwahrscheinlichkeit?
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{What is the actual symbol error probability&nbsp; $p_{\rm S}$?
 
|type="{}"}
 
|type="{}"}
$p_{\rm S}$ = { 0.19 3% }  
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$p_{\rm S}\ = \ $ { 0.19 3% }  
  
{Wie groß ist die Bitfehlerwahrscheinlichkeit bei Graycodierung?
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{What is the bit error probability&nbsp; $p_{\rm B}$&nbsp; for Gray coding?
 
|type="{}"}
 
|type="{}"}
$p_{\rm B}$ = { 0.1 3% }  
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$p_{\rm B}\ = \ $ { 0.1 3% }  
  
{Welcher Zusammenhang besteht zwischen $p_{\rm B}$ und $E_{\rm B}/N_0$?
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{What is the relationship between&nbsp; $p_{\rm B}$&nbsp; and &nbsp;$E_{\rm B}/N_0$?
|type="[]"}
+
|type="()"}
- $p_{\rm B} = {\rm Q}(\sqrt {E_{\rm B}/N_0})$,
+
- $p_{\rm B} = {\rm Q}\big [\sqrt {E_{\rm B}/N_0}\big ]$,
+ $p_{\rm B} = {\rm Q}(\sqrt {2E_{\rm B}/N_0})$,
+
+ $p_{\rm B} = {\rm Q}\big [\sqrt {2E_{\rm B}/N_0}\big ]$,
- $p_{\rm B} = {\rm Q}(\sqrt {E_{\rm B}/2N_0})$,
+
- $p_{\rm B} = {\rm Q}\big [\sqrt {E_{\rm B}/(2N_0)}\big ]$.
 
</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Die &bdquo;Union Bound&rdquo; ist eine obere Schranke für die mittlere Symbolfehlerwahrscheinlichkeit. Für letztere gilt:
+
'''(1)'''&nbsp; The&nbsp; "Union Bound"&nbsp; is an upper bound for the average symbol error probability.&nbsp; For the latter holds:
:$$p_{\rm S} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  {\rm Pr}({\cal{E}}) =  {\rm Pr}( {\cal{E}} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm gesendet})= $$
+
:$$p_{\rm S} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  {\rm Pr}({\cal{E}}) =  {\rm Pr}( {\cal{E}} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted})= {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted})
:$$ \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm entschieden} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm gesendet})
 
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Dagegen gilt für die (verbesserte) &bdquo;Union Bound&rdquo; im vorliegenden Beispiel:
+
*In contrast,&nbsp; for the&nbsp; (improved)&nbsp; "Union Bound"&nbsp; in the present example:
:$$p_{\rm UB} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}    {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C}  \hspace{0.15cm}{\rm entschieden} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm gesendet}) +$$
+
:$$p_{\rm UB} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}    {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C}  \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) +{\rm Pr}( \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D}  \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) = 2p = \underline{0.2}
:$$ \hspace{-0.1cm} \ + \ \hspace{-0.1cm}{\rm Pr}( \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D}  \hspace{0.15cm}{\rm entschieden} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm gesendet}) = 2p = \underline{0.2}
 
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
  
'''(2)'''&nbsp; Die beiden Wahrscheinlichkeiten, aus der sich die &bdquo;Union Bound&rdquo; additiv zusammensetzt, lassen sich geometrisch wie folgt deuten:
+
'''(2)'''&nbsp; The two probabilities that make up the&nbsp; "Union Bound"&nbsp; additive can be interpreted geometrically as follows:
* ${\rm Pr}(\boldsymbol{s}_{\rm B} \cup \boldsymbol{s}_{\rm C} | \boldsymbol{s}_{\rm A})$ ist die Wahrscheinlichkeit, dass der Empfangspunkt in der linken Halbebene liegt &nbsp;&#8658;&nbsp; die AWGN&ndash;Rauschkomponente $n_1$ ist negativ und betragsmäßig größer als $\sqrt {E}$.
+
* ${\rm Pr}(\boldsymbol{s}_{\rm B} \cup \boldsymbol{s}_{\rm C} | \boldsymbol{s}_{\rm A})$&nbsp; is the probability that the receiving point is located in the left half-plane <br> &#8658; &nbsp; the AWGN noise component&nbsp; $n_1$&nbsp; is negative and greater in magnitude than&nbsp; $\sqrt {E}$.
* ${\rm Pr}(\boldsymbol{s}_{\rm C} \cup \boldsymbol{s}_{\rm D} | \boldsymbol{s}_{\rm A})$ ist die Wahrscheinlichkeit, dass der Empfangspunkt in der unteren Halbebene liegt &nbsp;&#8658;&nbsp; die AWGN&ndash;Rauschkomponente $n_2$ ist negativ und betragsmäßig größer als $\sqrt {E}$.
+
 
 +
* ${\rm Pr}(\boldsymbol{s}_{\rm C} \cup \boldsymbol{s}_{\rm D} | \boldsymbol{s}_{\rm A})$&nbsp; is the probability that the receiving point lies in the lower half-plane <br> &#8658; &nbsp; the AWGN noise component&nbsp; $n_2$&nbsp; is negative and greater in magnitude than&nbsp; $\sqrt {E}$.
  
  
Das bedeutet, dass die &bdquo;Union Bound&rdquo; den dritten Quadranten zweimal berücksichtigt. Diesen Fehler kann man hier relativ einfach kompensieren:
+
Thus, the&nbsp; "Union Bound"&nbsp; considers the third quadrant twice.&nbsp; It is relatively easy to compensate for this error here:
:$$p_{\rm S} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  p_{\rm UB} -  {\rm Pr}( \boldsymbol{ s}_{\rm C}  \hspace{0.15cm}{\rm entschieden} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm gesendet}) = $$
+
:$$p_{\rm S} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  p_{\rm UB} -  {\rm Pr}( \boldsymbol{ s}_{\rm C}  \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) = 2 p -  {\rm Pr}\left [ ( n_1 < -\sqrt{E})\cap ( n_2 < -\sqrt{E})\right ] = 2p - p^2 = \underline{0.19}
:$$ \hspace{-0.1cm} \ = \ \hspace{-0.1cm} 2 p -  {\rm Pr}\left [ ( n_1 < -\sqrt{E})\cap ( n_2 < -\sqrt{E})\right ] = 2p - p^2 = \underline{0.19}
 
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Hierbei ist berücksichtigt, dass die Rauschkomponenten $n_1$ und $n_2$ voneinander unabhängig sind.
+
Here it is considered that the noise components&nbsp; $n_1$&nbsp; and&nbsp; $n_2$&nbsp; are independent of each other.
  
  
'''(3)'''&nbsp; Wie in der Teilaufgabe (2) nachgewiesen, gelten für die einzelnen Verfälschungswahrscheinlichkeiten:
+
'''(3)'''&nbsp; As proved in subtask&nbsp; '''(2)''',&nbsp; the following are valid for the individual falsification probabilities:
* Quadrant 2: ${\rm Pr}(\boldsymbol{s}_{\rm B} \  {\rm empfangen} \ | \ \boldsymbol{s}_{\rm A} \ {\rm gesendet}) = 0.09$,
+
* Quadrant 2:&nbsp; ${\rm Pr}(\boldsymbol{s}_{\rm B} \  {\rm received} \ | \ \boldsymbol{s}_{\rm A} \ {\rm transmitted}) = 0.09$,
* Quadrant 3: ${\rm Pr}(\boldsymbol{s}_{\rm C} \ {\rm empfangen} \ | \ \boldsymbol{s}_{\rm A} \ {\rm gesendet}) = 0.01$,
+
* Quadrant 3:&nbsp; ${\rm Pr}(\boldsymbol{s}_{\rm C} \ {\rm received} \ | \ \boldsymbol{s}_{\rm A} \ {\rm transmitted}) = 0.01$,
* Quadrant 4: ${\rm Pr}(\boldsymbol{s}_{\rm D} \ {\rm empfangen} \ | \ \boldsymbol{s}_{\rm A} \ {\rm gesendet}) = 0.09$.
+
* Quadrant 4:&nbsp; ${\rm Pr}(\boldsymbol{s}_{\rm D} \ {\rm received} \ | \ \boldsymbol{s}_{\rm A} \ {\rm transmitted}) = 0.09$.
  
  
Für die mittlere Bitfehlerwahrscheinlichkeit erhält man somit:
+
Thus,&nbsp; for the average bit error probability we obtain:
:$$p_{\rm B} = { 1}/{ 2} \cdot \left [ 1 \cdot 0.09 + 2 \cdot 0.01 + 1 \cdot 0.09\right ]= \underline{0.1} = p
+
:$$p_{\rm B} = { 1}/{ 2} \cdot \big [ 1 \cdot 0.09 + 2 \cdot 0.01 + 1 \cdot 0.09\big ]= \underline{0.1} = p
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Hierbei ist berücksichtigt, dass der Quadrant 2 und der Quadrant 4 jeweils nur zu einem Bitfehler führt, der Quadrant 3 dagegen zu zweien. Der Faktor $1/2$ berücksichtigt wieder, dass jeweils ein Symbol zwei Binärzeichen (Bit) beinhaltet.
+
*It is taken into account that&nbsp; "quadrant 2"&nbsp; and&nbsp; "quadrant 4"&nbsp; each lead to only one bit error,&nbsp; while&nbsp; "quadrant 3"&nbsp; leads to two.
 +
 
 +
*The factor&nbsp; $1/2$&nbsp; considers again that in each case one symbol contains two binary characters&nbsp; (bits).
  
  
'''(4)'''&nbsp; Die Bitfehlerwahrscheinlichkeit ist nach der Lösung zur Teilaufgabe (2) gleich der Wahrscheinlichkeit, dass die beiden Rauschkomponenten gewisse Grenzen überschreiten:
+
'''(4)'''&nbsp; According to the solution to subtask&nbsp; '''(2)''',&nbsp; the bit error probability is equal to the probability that the two noise components exceed certain limits:
 
:$$p_{\rm B}  = {\rm Pr}( n_1 < -\sqrt{E}) = {\rm Pr}( n_2 < -\sqrt{E})
 
:$$p_{\rm B}  = {\rm Pr}( n_1 < -\sqrt{E}) = {\rm Pr}( n_2 < -\sqrt{E})
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Beim AWGN&ndash;Kanal lautet diese Wahrscheinlichkeit mit der Varianz $\sigma_n^2 = N_0/2$:
+
*For the AWGN channel,&nbsp; this probability with variance&nbsp; $\sigma_n^2 = N_0/2$&nbsp; is:
 
:$$p_{\rm B} = {\rm Q} \left ( { { \sqrt{E}}/{ \sigma_n} }\right ) =  {\rm Q} \left ( \sqrt{ { {2E}}/{ N_0} }\right )
 
:$$p_{\rm B} = {\rm Q} \left ( { { \sqrt{E}}/{ \sigma_n} }\right ) =  {\rm Q} \left ( \sqrt{ { {2E}}/{ N_0} }\right )
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Die mittlere Energie pro Symbol kann am einfachsten durch Mittelung über die quadratischen Abstände der Signalraumpunkte vom Ursprung bestimmt werden und ergibt $E_{\rm S} = 2E$. Die mittlere Energie pro Bit ist halb so groß: $E_{\rm B} = E_{\rm S}/2 = E$. Daraus folgt:
+
*The average energy per symbol can be most easily determined by averaging over the squared distances of the signal space points from the origin.&nbsp; <br>This yields&nbsp; $E_{\rm S} = 2E$.
 +
 +
*The average energy per bit is half:&nbsp; $E_{\rm B} = E_{\rm S}/2 = E$.&nbsp; From this follows:
 
:$$p_{\rm B}  =  {\rm Q} \left ( \sqrt{ { {2E_{\rm B}}}/{ N_0} }\right )
 
:$$p_{\rm B}  =  {\rm Q} \left ( \sqrt{ { {2E_{\rm B}}}/{ N_0} }\right )
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Richtig ist also der <u>zweite Lösungsvorschlag</u>. Zum gleichen Ergebnis kommt man auch, wenn man die 4&ndash;QAM wie im Kapitel [[Digitalsignal%C3%BCbertragung/Struktur_des_optimalen_Empf%C3%A4ngers| Struktur des optimalen Empfängers]] des Buches &bdquo;Modulationsverfahren&rdquo; als zwei orthogonale (das heißt: sich nicht störende) BPSK&ndash;Systeme über den gleichen Kanal betrachtet.
+
*The&nbsp; <u>second solution</u>&nbsp; is therefore correct.
 +
 +
*The same result is also obtained if the&nbsp; "4&ndash;QAM"&nbsp; is considered as two orthogonal&nbsp; (i.e.:&nbsp; not interfering with each other)&nbsp; BPSK systems over the same channel as in the chapter&nbsp; [[Digital_Signal_Transmission/Structure_of_the_Optimal_Receiver|"Structure of the Optimal Receiver"]]&nbsp; of the book&nbsp; "Modulation methods".
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Digitalsignalübertragung|^4.4 Kohärente Demodulation^]]
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[[Category:Digital Signal Transmission: Exercises|^4.4 Coherent Demodulation^]]

Latest revision as of 13:03, 21 August 2022

Signal space constellation  "4–QAM"

We now consider a quadrature amplitude modulation with  $M = 4$  symbols and the  (normalized)  signal space points

$$\boldsymbol{ s}_{\rm A} = (+1, +1)\hspace{0.05cm},\hspace{0.2cm}\boldsymbol{ s}_{\rm B} = (-1, +1)\hspace{0.05cm},\hspace{0.2cm} \boldsymbol{ s}_{\rm C} = (-1, -1)\hspace{0.05cm},\hspace{0.2cm}\boldsymbol{ s}_{\rm D} = (+1, -1) \hspace{0.05cm}.$$

The symbols are equally probable.  Thus,  averaging can be omitted to calculate the average symbol error probability.

For example:

$$p_{\rm S} = {\rm Pr}({\cal{E}}) = {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) \hspace{0.05cm}.$$

The assignment of the symbols to  "bit-duples"  can also be taken from the graphic  (red labels).  Gray coding is assumed here.




Notes:

  • For subtask  (4),  the (discrete-time) AWGN channel with variance  $\sigma_n^2 = N_0/2$  is assumed.
  • For the probability that a symbol is falsified horizontally or vertically by the noise signal  $n$,  with the complementary Gaussian error function  $\rm Q(x)$ holds:
$$p = {\rm Pr}( n < -x_0) = {\rm Pr}( n > + x_0) = {\rm Q}(x_0 / \sigma_n) \hspace{0.05cm}.$$



Questions

1

Give the  "Union Bound"  as the upper bound for the symbol error probability  $p_{\rm S}$   $(p_{\rm UB} ≥ p_{\rm S})$.  Let  $p = 0.1$.

$p_{\rm UB}\ = \ $

2

What is the actual symbol error probability  $p_{\rm S}$?

$p_{\rm S}\ = \ $

3

What is the bit error probability  $p_{\rm B}$  for Gray coding?

$p_{\rm B}\ = \ $

4

What is the relationship between  $p_{\rm B}$  and  $E_{\rm B}/N_0$?

$p_{\rm B} = {\rm Q}\big [\sqrt {E_{\rm B}/N_0}\big ]$,
$p_{\rm B} = {\rm Q}\big [\sqrt {2E_{\rm B}/N_0}\big ]$,
$p_{\rm B} = {\rm Q}\big [\sqrt {E_{\rm B}/(2N_0)}\big ]$.


Solution

(1)  The  "Union Bound"  is an upper bound for the average symbol error probability.  For the latter holds:

$$p_{\rm S} \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {\rm Pr}({\cal{E}}) = {\rm Pr}( {\cal{E}} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted})= {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) \hspace{0.05cm}.$$
  • In contrast,  for the  (improved)  "Union Bound"  in the present example:
$$p_{\rm UB} \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {\rm Pr}( \boldsymbol{ s}_{\rm B} \cup \boldsymbol{ s}_{\rm C} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) +{\rm Pr}( \boldsymbol{ s}_{\rm C} \cup \boldsymbol{ s}_{\rm D} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) = 2p = \underline{0.2} \hspace{0.05cm}.$$


(2)  The two probabilities that make up the  "Union Bound"  additive can be interpreted geometrically as follows:

  • ${\rm Pr}(\boldsymbol{s}_{\rm B} \cup \boldsymbol{s}_{\rm C} | \boldsymbol{s}_{\rm A})$  is the probability that the receiving point is located in the left half-plane
    ⇒   the AWGN noise component  $n_1$  is negative and greater in magnitude than  $\sqrt {E}$.
  • ${\rm Pr}(\boldsymbol{s}_{\rm C} \cup \boldsymbol{s}_{\rm D} | \boldsymbol{s}_{\rm A})$  is the probability that the receiving point lies in the lower half-plane
    ⇒   the AWGN noise component  $n_2$  is negative and greater in magnitude than  $\sqrt {E}$.


Thus, the  "Union Bound"  considers the third quadrant twice.  It is relatively easy to compensate for this error here:

$$p_{\rm S} \hspace{-0.1cm} \ = \ \hspace{-0.1cm} p_{\rm UB} - {\rm Pr}( \boldsymbol{ s}_{\rm C} \hspace{0.15cm}{\rm decided} \hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s}_{\rm A}\hspace{0.15cm} {\rm transmitted}) = 2 p - {\rm Pr}\left [ ( n_1 < -\sqrt{E})\cap ( n_2 < -\sqrt{E})\right ] = 2p - p^2 = \underline{0.19} \hspace{0.05cm}.$$

Here it is considered that the noise components  $n_1$  and  $n_2$  are independent of each other.


(3)  As proved in subtask  (2),  the following are valid for the individual falsification probabilities:

  • Quadrant 2:  ${\rm Pr}(\boldsymbol{s}_{\rm B} \ {\rm received} \ | \ \boldsymbol{s}_{\rm A} \ {\rm transmitted}) = 0.09$,
  • Quadrant 3:  ${\rm Pr}(\boldsymbol{s}_{\rm C} \ {\rm received} \ | \ \boldsymbol{s}_{\rm A} \ {\rm transmitted}) = 0.01$,
  • Quadrant 4:  ${\rm Pr}(\boldsymbol{s}_{\rm D} \ {\rm received} \ | \ \boldsymbol{s}_{\rm A} \ {\rm transmitted}) = 0.09$.


Thus,  for the average bit error probability we obtain:

$$p_{\rm B} = { 1}/{ 2} \cdot \big [ 1 \cdot 0.09 + 2 \cdot 0.01 + 1 \cdot 0.09\big ]= \underline{0.1} = p \hspace{0.05cm}.$$
  • It is taken into account that  "quadrant 2"  and  "quadrant 4"  each lead to only one bit error,  while  "quadrant 3"  leads to two.
  • The factor  $1/2$  considers again that in each case one symbol contains two binary characters  (bits).


(4)  According to the solution to subtask  (2),  the bit error probability is equal to the probability that the two noise components exceed certain limits:

$$p_{\rm B} = {\rm Pr}( n_1 < -\sqrt{E}) = {\rm Pr}( n_2 < -\sqrt{E}) \hspace{0.05cm}.$$
  • For the AWGN channel,  this probability with variance  $\sigma_n^2 = N_0/2$  is:
$$p_{\rm B} = {\rm Q} \left ( { { \sqrt{E}}/{ \sigma_n} }\right ) = {\rm Q} \left ( \sqrt{ { {2E}}/{ N_0} }\right ) \hspace{0.05cm}.$$
  • The average energy per symbol can be most easily determined by averaging over the squared distances of the signal space points from the origin. 
    This yields  $E_{\rm S} = 2E$.
  • The average energy per bit is half:  $E_{\rm B} = E_{\rm S}/2 = E$.  From this follows:
$$p_{\rm B} = {\rm Q} \left ( \sqrt{ { {2E_{\rm B}}}/{ N_0} }\right ) \hspace{0.05cm}.$$
  • The  second solution  is therefore correct.
  • The same result is also obtained if the  "4–QAM"  is considered as two orthogonal  (i.e.:  not interfering with each other)  BPSK systems over the same channel as in the chapter  "Structure of the Optimal Receiver"  of the book  "Modulation methods".