Difference between revisions of "Aufgaben:Exercise 2.2: Distortion Power"
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− | {{quiz-Header|Buchseite= | + | {{quiz-Header|Buchseite=Linear_and_Time_Invariant_Systems/Classification_of_the_Distortions |
}} | }} | ||
− | [[File:P_ID883__LZI_A_2_2.png|right|frame| | + | [[File:P_ID883__LZI_A_2_2.png|right|frame|Input signal and output signals]] |
− | + | A rectangular pulse $x(t)$ with amplitude $1 \hspace{0.08cm} \rm V$ and duration $4 \hspace{0.08cm} \rm ms$ is applied to the input of a communication system. Then, the pulse $y_1(t)$ , whose signal parameters can be taken from the middle sketch, is measured at the system output. | |
− | + | At the output of another system $S_2$ , the signal $y_2(t)$ shown in the lower sketch is obtained with the same input signal $x(t)$ . | |
− | + | Let the following definition apply to the error signal used in this task: | |
:$$\varepsilon(t) = y(t) - \alpha \cdot x(t - \tau) .$$ | :$$\varepsilon(t) = y(t) - \alpha \cdot x(t - \tau) .$$ | ||
− | + | The parameters $\alpha$ and $\tau$ are to be determined such that the distortion power (the mean squared error) is minimal. For this, the following holds: | |
:$$P_{\rm V} = \overline{\varepsilon^2(t)} = \frac{1}{T_{\rm M}} \cdot \int\limits_{ ( T_{\rm M})} | :$$P_{\rm V} = \overline{\varepsilon^2(t)} = \frac{1}{T_{\rm M}} \cdot \int\limits_{ ( T_{\rm M})} | ||
{\varepsilon^2(t) }\hspace{0.1cm}{\rm d}t$$ | {\varepsilon^2(t) }\hspace{0.1cm}{\rm d}t$$ | ||
− | + | These definitions already take into account that a frequency-independent damping just as a runtime which is constant for all frequencies does not contribute to the distortion. | |
− | + | The integration interval has to be chosen appropriately in each case: | |
− | * | + | *Use the interval $0$ ... $4 \hspace{0.08cm} \rm ms$ for $y_1(t)$ and the interval $1 \hspace{0.08cm} {\rm ms}$ ... $5 \hspace{0.08cm} \rm ms$ for $y_2(t)$ . |
− | * | + | *Thus, the measurement time is $T_{\rm M} = 4 \hspace{0.08cm} \rm ms$ in both cases. |
− | * | + | *It is obvious that with respect to $y_1(t)$ the parameters $\alpha = 1$ and $\tau = 0$ respectively result in the minimum distortion power. |
− | + | In general, the so-called signal–to–distortion–power ratio is given by the following formula | |
:$$\rho_{\rm V} = \frac{ \alpha^2 \cdot P_{x}}{P_{\rm V}} \hspace{0.05cm}.$$ | :$$\rho_{\rm V} = \frac{ \alpha^2 \cdot P_{x}}{P_{\rm V}} \hspace{0.05cm}.$$ | ||
− | + | Here, | |
− | *$P_x$ | + | *$P_x$ denotes the power of the signal $x(t)$, and |
− | *$\alpha^2 \cdot P_x$ | + | *$\alpha^2 \cdot P_x$ denotes the power of $y(t) = \alpha \cdot x(t - \tau)$, that would arise as aresult in the absence of distortion. |
− | + | Usually, – as also in this task– this S/N-ratio $\rho_{\rm V}$ is given logarithmically in $\rm dB$ . | |
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− | '' | + | ''Please note:'' |
− | * | + | *The exercise belongs to the chapter [[Linear_and_Time_Invariant_Systems/Classification_of_the_Distortions|Classification of the Distortions]]. |
− | * | + | *In particular, consider the pages |
− | ::[[Linear_and_Time_Invariant_Systems/ | + | ::[[Linear_and_Time_Invariant_Systems/Classification_of_the_Distortions#Quantitative_measure_for_the_signal_distortions|Quantitative measure for the signal distortions]] and also |
− | ::[[Linear_and_Time_Invariant_Systems/ | + | ::[[Linear_and_Time_Invariant_Systems/Classification_of_the_Distortions#Ber.C3.BCcksichtigung_von_D.C3.A4mpfung_und_Laufzeit|Berücksichtigung von Dämpfung und Laufzeit]]. |
− | === | + | ===Questions=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {Determine the distortion power of the system $S_1$. |
|type="{}"} | |type="{}"} | ||
$P_{\rm V1} \ = \ $ { 5 3% } $\ \cdot 10^{-3} \ {\rm V}^2$ | $P_{\rm V1} \ = \ $ { 5 3% } $\ \cdot 10^{-3} \ {\rm V}^2$ | ||
− | { | + | {Compute the signal–to–distortion–power ratio for system $S_1$. |
|type="{}"} | |type="{}"} | ||
$10 \cdot {\rm lg} \ \rho_\text{V1} \ = \ $ { 23.01 3% } $\ \rm dB$ | $10 \cdot {\rm lg} \ \rho_\text{V1} \ = \ $ { 23.01 3% } $\ \rm dB$ | ||
− | { | + | {What parameters $\alpha$ and $\tau$ should be used to calculate the distortion power of the system $S_2$ ? <br>Justify your result. |
|type="{}"} | |type="{}"} | ||
$\alpha \ = \ $ { 0.5 3% } | $\alpha \ = \ $ { 0.5 3% } | ||
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− | { | + | {Determine the distortion power of the system $S_2$. |
|type="{}"} | |type="{}"} | ||
$P_{\rm V2} \ = \ $ { 5 3% } $\ \cdot 10^{-3} \ {\rm V}^2$ | $P_{\rm V2} \ = \ $ { 5 3% } $\ \cdot 10^{-3} \ {\rm V}^2$ | ||
− | { | + | {Compute the signal–to–distortion–power ratio for the system $S_2$. <br>Interpret the different results. |
|type="{}"} | |type="{}"} | ||
$10 \cdot {\rm lg} \ \rho_\text{V2} \ = \ $ { 16.99 3% } $\ \rm dB$ | $10 \cdot {\rm lg} \ \rho_\text{V2} \ = \ $ { 16.99 3% } $\ \rm dB$ | ||
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</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | [[File:P_ID915__LZI_A_2_2_a.png|right|frame| | + | [[File:P_ID915__LZI_A_2_2_a.png|right|frame|Resulting error signals]] |
− | '''(1)''' | + | '''(1)''' The error signal $\varepsilon_1(t)$ shown in the graph is obtained with the given parameters $\alpha = 1$ and $\tau= 0$ . The distortion power is thus equal to: |
:$$P_{\rm V1} = \frac{ {1 \, \rm ms}}{4 \, \rm ms} \cdot \big[ ({0.1 \, \rm V})^2 + | :$$P_{\rm V1} = \frac{ {1 \, \rm ms}}{4 \, \rm ms} \cdot \big[ ({0.1 \, \rm V})^2 + | ||
({-0.1 \, \rm V})^2\big]\hspace{0.3cm}\Rightarrow \hspace{0.3cm}P_{\rm V1} \hspace{0.15cm}\underline{ = 5 \cdot 10^{-3} \, \rm V^2}. $$ | ({-0.1 \, \rm V})^2\big]\hspace{0.3cm}\Rightarrow \hspace{0.3cm}P_{\rm V1} \hspace{0.15cm}\underline{ = 5 \cdot 10^{-3} \, \rm V^2}. $$ | ||
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− | '''(2)''' | + | '''(2)''' The power of the input signal is: |
:$$P_{x} = \frac{1}{4 \, \rm ms} \cdot ({1 \, \rm V})^2 \cdot {4 \, \rm ms}\hspace{0.15cm}{ = {1 \, \rm V^2}}.$$ | :$$P_{x} = \frac{1}{4 \, \rm ms} \cdot ({1 \, \rm V})^2 \cdot {4 \, \rm ms}\hspace{0.15cm}{ = {1 \, \rm V^2}}.$$ | ||
− | * | + | *The following is obtained for the signal–to–distortion–power ratio with the result from '''(1)''' : |
$$\rho_{\rm V1} = \frac{ P_{x}}{P_{\rm V1}}= \frac{ {1 \, \rm | $$\rho_{\rm V1} = \frac{ P_{x}}{P_{\rm V1}}= \frac{ {1 \, \rm | ||
V^2}}{0.005 \, \rm V^2}\hspace{0.05cm}\rm = 200\hspace{0.3cm} \Rightarrow \hspace{0.3cm} | V^2}}{0.005 \, \rm V^2}\hspace{0.05cm}\rm = 200\hspace{0.3cm} \Rightarrow \hspace{0.3cm} | ||
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− | '''(3)''' | + | '''(3)''' The sketch on the information sheet makes it clear that even without the distortions occuring – but due to attenuation and runtime alone – the signal $y(t)$ would differ significantly from $x(t)$ . |
− | * | + | *The following would arise as a result: $y(t) = 0.5 \cdot x(t-1\ {\rm ms}) $ . |
− | * | + | *If someone does not immediately perceive these values from the graph, then first the error signal |
:$$\varepsilon_2(t) = y_2(t) - \alpha \cdot x(t - \tau)$$ | :$$\varepsilon_2(t) = y_2(t) - \alpha \cdot x(t - \tau)$$ | ||
− | : | + | :and afterwards the mean squared error for very (infinitely) many $\alpha$– and $\tau$–values would have to be determined, in doing so the integration interval is to be adjusted to $\tau$ in each case. |
− | * | + | *Then, the smallest possible result would also be obtained for $\alpha \; \underline{= 0.5}$ and $\tau \; \underline{= 1 \ \rm ms}$ . However, for this optimization of $\alpha$ and $\tau$ the useage of a computer program should be granted. |
− | '''(4)''' | + | '''(4)''' The above sketch shows that $\varepsilon_2(t)$ is equal to the error signal $\varepsilon_1(t)$ except for a shift by $1 \ \rm ms$ . Considering the integration interval $1 \ {\rm ms}$ ... $5 \ {\rm ms}$ the same distortion power is obtained: |
:$$P_{\rm V2} = P_{\rm V1} \hspace{0.15cm}\underline{ = 5 \cdot 10^{-3} \, \rm V^2}.$$ | :$$P_{\rm V2} = P_{\rm V1} \hspace{0.15cm}\underline{ = 5 \cdot 10^{-3} \, \rm V^2}.$$ | ||
− | '''(5)''' | + | '''(5)''' According to the information sheet the following holds: |
:$$\rho_{\rm V2} = \frac{ \alpha^2 \cdot P_{x}}{P_{\rm V2}}= \frac{ 0.5^2 \cdot {1 \, \rm | :$$\rho_{\rm V2} = \frac{ \alpha^2 \cdot P_{x}}{P_{\rm V2}}= \frac{ 0.5^2 \cdot {1 \, \rm | ||
V^2}}{0.005 \, \rm V^2}\hspace{0.05cm}\rm = 50\hspace{0.3cm} \Rightarrow \hspace{0.3cm} | V^2}}{0.005 \, \rm V^2}\hspace{0.05cm}\rm = 50\hspace{0.3cm} \Rightarrow \hspace{0.3cm} | ||
10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V2} \hspace{0.15cm}\underline{= {16.99 \, \rm dB}}.$$ | 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V2} \hspace{0.15cm}\underline{= {16.99 \, \rm dB}}.$$ | ||
− | * | + | *Despite the same distortion power $10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V2}$ is less than $10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V1}$ by about $6 \ \rm dB$ . |
− | * | + | *The signal $y_2(t)$ is thus significantly less favourable in terms of SNR than $y_1(t)$. |
− | * | + | *It is considered that now the power of the output signal is only a quarter of the input power due to $\alpha = 0.5$ . |
− | * | + | *If this attenuation at the output was to be compensated by amplifying it by $1/\alpha$, the distortion power would indeed increase by $\alpha^2$. |
− | * | + | *The signal-to-distortion-power ratio $\rho_{\rm V2}$ would, however, remain the same because the "useful signal" would also be increased by the same value. |
{{ML-Fuß}} | {{ML-Fuß}} | ||
Latest revision as of 21:51, 12 September 2021
A rectangular pulse $x(t)$ with amplitude $1 \hspace{0.08cm} \rm V$ and duration $4 \hspace{0.08cm} \rm ms$ is applied to the input of a communication system. Then, the pulse $y_1(t)$ , whose signal parameters can be taken from the middle sketch, is measured at the system output.
At the output of another system $S_2$ , the signal $y_2(t)$ shown in the lower sketch is obtained with the same input signal $x(t)$ .
Let the following definition apply to the error signal used in this task:
- $$\varepsilon(t) = y(t) - \alpha \cdot x(t - \tau) .$$
The parameters $\alpha$ and $\tau$ are to be determined such that the distortion power (the mean squared error) is minimal. For this, the following holds:
- $$P_{\rm V} = \overline{\varepsilon^2(t)} = \frac{1}{T_{\rm M}} \cdot \int\limits_{ ( T_{\rm M})} {\varepsilon^2(t) }\hspace{0.1cm}{\rm d}t$$
These definitions already take into account that a frequency-independent damping just as a runtime which is constant for all frequencies does not contribute to the distortion.
The integration interval has to be chosen appropriately in each case:
- Use the interval $0$ ... $4 \hspace{0.08cm} \rm ms$ for $y_1(t)$ and the interval $1 \hspace{0.08cm} {\rm ms}$ ... $5 \hspace{0.08cm} \rm ms$ for $y_2(t)$ .
- Thus, the measurement time is $T_{\rm M} = 4 \hspace{0.08cm} \rm ms$ in both cases.
- It is obvious that with respect to $y_1(t)$ the parameters $\alpha = 1$ and $\tau = 0$ respectively result in the minimum distortion power.
In general, the so-called signal–to–distortion–power ratio is given by the following formula
- $$\rho_{\rm V} = \frac{ \alpha^2 \cdot P_{x}}{P_{\rm V}} \hspace{0.05cm}.$$
Here,
- $P_x$ denotes the power of the signal $x(t)$, and
- $\alpha^2 \cdot P_x$ denotes the power of $y(t) = \alpha \cdot x(t - \tau)$, that would arise as aresult in the absence of distortion.
Usually, – as also in this task– this S/N-ratio $\rho_{\rm V}$ is given logarithmically in $\rm dB$ .
Please note:
- The exercise belongs to the chapter Classification of the Distortions.
- In particular, consider the pages
Questions
Solution
(1) The error signal $\varepsilon_1(t)$ shown in the graph is obtained with the given parameters $\alpha = 1$ and $\tau= 0$ . The distortion power is thus equal to:
- $$P_{\rm V1} = \frac{ {1 \, \rm ms}}{4 \, \rm ms} \cdot \big[ ({0.1 \, \rm V})^2 + ({-0.1 \, \rm V})^2\big]\hspace{0.3cm}\Rightarrow \hspace{0.3cm}P_{\rm V1} \hspace{0.15cm}\underline{ = 5 \cdot 10^{-3} \, \rm V^2}. $$
(2) The power of the input signal is:
- $$P_{x} = \frac{1}{4 \, \rm ms} \cdot ({1 \, \rm V})^2 \cdot {4 \, \rm ms}\hspace{0.15cm}{ = {1 \, \rm V^2}}.$$
- The following is obtained for the signal–to–distortion–power ratio with the result from (1) :
$$\rho_{\rm V1} = \frac{ P_{x}}{P_{\rm V1}}= \frac{ {1 \, \rm V^2}}{0.005 \, \rm V^2}\hspace{0.05cm}\rm = 200\hspace{0.3cm} \Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V1}\hspace{0.15cm}\underline{ = {23.01 \, \rm dB}}.$$
(3) The sketch on the information sheet makes it clear that even without the distortions occuring – but due to attenuation and runtime alone – the signal $y(t)$ would differ significantly from $x(t)$ .
- The following would arise as a result: $y(t) = 0.5 \cdot x(t-1\ {\rm ms}) $ .
- If someone does not immediately perceive these values from the graph, then first the error signal
- $$\varepsilon_2(t) = y_2(t) - \alpha \cdot x(t - \tau)$$
- and afterwards the mean squared error for very (infinitely) many $\alpha$– and $\tau$–values would have to be determined, in doing so the integration interval is to be adjusted to $\tau$ in each case.
- Then, the smallest possible result would also be obtained for $\alpha \; \underline{= 0.5}$ and $\tau \; \underline{= 1 \ \rm ms}$ . However, for this optimization of $\alpha$ and $\tau$ the useage of a computer program should be granted.
(4) The above sketch shows that $\varepsilon_2(t)$ is equal to the error signal $\varepsilon_1(t)$ except for a shift by $1 \ \rm ms$ . Considering the integration interval $1 \ {\rm ms}$ ... $5 \ {\rm ms}$ the same distortion power is obtained:
- $$P_{\rm V2} = P_{\rm V1} \hspace{0.15cm}\underline{ = 5 \cdot 10^{-3} \, \rm V^2}.$$
(5) According to the information sheet the following holds:
- $$\rho_{\rm V2} = \frac{ \alpha^2 \cdot P_{x}}{P_{\rm V2}}= \frac{ 0.5^2 \cdot {1 \, \rm V^2}}{0.005 \, \rm V^2}\hspace{0.05cm}\rm = 50\hspace{0.3cm} \Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V2} \hspace{0.15cm}\underline{= {16.99 \, \rm dB}}.$$
- Despite the same distortion power $10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V2}$ is less than $10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm V1}$ by about $6 \ \rm dB$ .
- The signal $y_2(t)$ is thus significantly less favourable in terms of SNR than $y_1(t)$.
- It is considered that now the power of the output signal is only a quarter of the input power due to $\alpha = 0.5$ .
- If this attenuation at the output was to be compensated by amplifying it by $1/\alpha$, the distortion power would indeed increase by $\alpha^2$.
- The signal-to-distortion-power ratio $\rho_{\rm V2}$ would, however, remain the same because the "useful signal" would also be increased by the same value.