Difference between revisions of "Aufgaben:Exercise 2.4: Dual Code and Gray Code"
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*Reference is also made to the chapter [[Digital_Signal_Transmission/Redundanzfreie_Codierung|"Redundancy-Free Coding"]]. | *Reference is also made to the chapter [[Digital_Signal_Transmission/Redundanzfreie_Codierung|"Redundancy-Free Coding"]]. | ||
− | *For numerical evaluation of the Q–function you can use the HTML5/JavaScript applet [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen|Complementary Gaussian Error Functions]]. | + | *For numerical evaluation of the Q–function you can use the HTML5/JavaScript applet [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen|"Complementary Gaussian Error Functions"]]. |
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===Solution=== | ===Solution=== | ||
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(1)''' In the signal s2(t) one recognizes the realization of the dual code indicated at the beginning. On the other hand, in the signal s2(t) a | + | '''(1)''' In the signal s2(t) one recognizes the realization of the dual code indicated at the beginning. On the other hand, in the signal s2(t) a Gray code ⇒ <u>solution 1</u> with the following mapping was used: |
:HH⇔−1,HL⇔−1/3,LL⇔+1/3,LH⇔+1. | :HH⇔−1,HL⇔−1/3,LL⇔+1/3,LH⇔+1. | ||
− | '''(2)''' Let the probability p that the amplitude value 3V falls below the adjacent decision threshold 2V due to the Gaussian distributed noise with standard deviation σd be 1%. It follows that: | + | '''(2)''' Let the probability p that the amplitude value 3V falls below the adjacent decision threshold 2V due to the Gaussian distributed noise with standard deviation σd be 1%. It follows that: |
:p=Q(3V−2Vσd)=1%⇒1V/σd≈2.33⇒σd≈0.43V_. | :p=Q(3V−2Vσd)=1%⇒1V/σd≈2.33⇒σd≈0.43V_. | ||
− | '''(3)''' The two outer symbols are each | + | '''(3)''' The two outer symbols are each falsified with probability p, the two inner symbols with double probability (2p). By averaging considering equal symbol occurrence probabilities, we obtain |
:pS=1.5⋅p=1.5%_. | :pS=1.5⋅p=1.5%_. | ||
− | '''(4)''' Each symbol error results in exactly one bit error. However, since each quaternary symbol contains exactly two binary symbols, the bit error probability is obtained: | + | '''(4)''' Each symbol error results in exactly one bit error. However, since each quaternary symbol contains exactly two binary symbols, the bit error probability is obtained: |
:pB=pS/2=0.75%_. | :pB=pS/2=0.75%_. | ||
− | '''(5)''' When calculating the symbol error probability pS, the mapping used is not taken into account. As in subtask '''(3)''', we obtain pS=1.5%_. | + | '''(5)''' When calculating the symbol error probability pS, the mapping used is not taken into account. As in subtask '''(3)''', we obtain pS=1.5%_. |
− | '''(6)''' The two outer symbols are | + | '''(6)''' The two outer symbols are falsified with p and lead to only one bit error each even with dual code. |
− | * The inner symbols are | + | * The inner symbols are falsified with 2p and now lead to 1.5 bit errors on average. |
− | *Taking into account the factor 2 in the denominator – see subtask '''(2)''' – we thus obtain for the bit error probability of the dual code: | + | *Taking into account the factor 2 in the denominator – see subtask '''(2)''' – we thus obtain for the bit error probability of the dual code: |
:pB=14⋅p+2p⋅1.5+2p⋅1.5+p2=p=1%_. | :pB=14⋅p+2p⋅1.5+2p⋅1.5+p2=p=1%_. | ||
Latest revision as of 17:46, 16 May 2022
The two shown signals s1(t) and s2(t) are two different realizations of a redundancy-free quaternary transmitted signal, both derived from the blue drawn binary source signal q(t).
For one of the transmitted signals, the so-called dual code with mapping
- LL⇔−s0,LH⇔−s0/3,HL⇔+s0/3,HH⇔+s0
was used, for the other one a certain form of a Gray code. This is characterized by the fact that the binary representation of adjacent amplitude values always differ only in a single bit.
The solution of the exercise should be based on the following assumptions:
- The amplitude levels are ±3V and ±1V.
- The decision thresholds lie in the middle between two adjacent amplitude values, i.e. at –2\, \rm V, 0\, \rm V and +2\, \rm V.
- The noise rms value \sigma_{d} is to be chosen so that the falsification probability from the outer symbol (+s_0) to the nearest symbol (+s_{0}/3) is exactly p = 1\%.
- Falsification to non-adjacent symbols can be excluded; in the case of Gaussian perturbations, this simplification is always allowed in practice.
One distinguishes in principle between
- the "symbol error probability" p_{\rm S} (related to the quaternary signal) and
- the "bit error probability" p_{B} (related to the binary source signal).
Notes:
- The exercise is part of the chapter "Basics of Coded Transmission".
- Reference is also made to the chapter "Redundancy-Free Coding".
- For numerical evaluation of the Q–function you can use the HTML5/JavaScript applet "Complementary Gaussian Error Functions".
Questions
Solution
- \mathbf{HH}\hspace{0.1cm}\Leftrightarrow \hspace{0.1cm} -1, \hspace{0.35cm} \mathbf{HL}\hspace{0.1cm}\Leftrightarrow \hspace{0.1cm} -1/3, \hspace{0.35cm} \mathbf{LL}\hspace{0.1cm}\Leftrightarrow \hspace{0.1cm} +1/3, \hspace{0.35cm} \mathbf{LH}\hspace{0.1cm}\Leftrightarrow \hspace{0.1cm} +1 \hspace{0.05cm}.
(2) Let the probability p that the amplitude value 3 \, \rm V falls below the adjacent decision threshold 2\, \rm V due to the Gaussian distributed noise with standard deviation \sigma_{d} be 1\, \%. It follows that:
- p = {\rm Q} \left ( \frac{3\,{\rm V} - 2\,{\rm V}} { \sigma_d}\right ) = 1 \%\hspace{0.3cm}\Rightarrow \hspace{0.3cm} {1\,{\rm V} }/ { \sigma_d} \approx 2.33 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} { \sigma_d}\hspace{0.15cm}\underline {\approx 0.43\,{\rm V}}\hspace{0.05cm}.
(3) The two outer symbols are each falsified with probability p, the two inner symbols with double probability (2p). By averaging considering equal symbol occurrence probabilities, we obtain
- p_{\rm S} = 1.5 \cdot p \hspace{0.15cm}\underline { = 1.5 \,\%} \hspace{0.05cm}.
(4) Each symbol error results in exactly one bit error. However, since each quaternary symbol contains exactly two binary symbols, the bit error probability is obtained:
- p_{\rm B} = {p_{\rm S}}/ { 2}\hspace{0.15cm}\underline { = 0.75 \,\%} \hspace{0.05cm}.
(5) When calculating the symbol error probability p_{\rm S}, the mapping used is not taken into account. As in subtask (3), we obtain p_{\rm S} \hspace{0.15cm}\underline{ = 1.5 \, \%}.
(6) The two outer symbols are falsified with p and lead to only one bit error each even with dual code.
- The inner symbols are falsified with 2p and now lead to 1.5 bit errors on average.
- Taking into account the factor 2 in the denominator – see subtask (2) – we thus obtain for the bit error probability of the dual code:
- p_{\rm B} = \frac{1} { 4} \cdot \frac{p + 2p \cdot 1.5 + 2p \cdot 1.5 + p} { 2} = p \hspace{0.15cm}\underline { = 1 \,\%} \hspace{0.05cm}.