Difference between revisions of "Aufgaben:Exercise 4.4: About the Quantization Noise"
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− | {{quiz-Header|Buchseite= | + | {{quiz-Header|Buchseite=Modulation_Methods/Pulse_Code_Modulation |
}} | }} | ||
− | [[File:P_ID1616__Mod_A_4_4.png|right|frame| | + | [[File:P_ID1616__Mod_A_4_4.png|right|frame|Quantization error with sawtooth input]] |
− | + | To calculate the quantization noise power $P_{\rm Q}$ we assume a periodic sawtooth-shaped source signal $q(t)$ with value range $±q_{\rm max}$ and period duration $T_0$ . | |
− | * | + | *In the mean time domain $-T_0/2 ≤ t ≤ T_0/2$ holds: $q(t) = q_{\rm max} \cdot \left ( {2 \cdot t}/{T_0} \right ).$ |
− | * | + | *We refer to the power of the signal $q(t)$ here as the transmit power $P_{\rm S}$. |
− | + | The signal $q(t)$ is quantized according to the graph with $M = 6$ stages. The quantized signal is $q_{\rm Q}(t)$, where: | |
− | * | + | *The linear quantizer is designed for the amplitude range $±Q_{\rm max}$ such that each quantization interval has width ${\it Δ} = 2/M - Q_{\rm max}$ . |
− | * | + | *The diagram shows this fact for $Q_{\rm max} = q_{\rm max} = 6 \ \rm V$. These numerical values shall be assumed up to and including the subtask '''(5)''' . |
− | + | The so-called '''quantization noise power''' is defined as the root mean square of the difference signal $ε(t) = q_{\rm Q}(t) - q(t)$ . It holds | |
:$$P_{\rm Q} = \frac{1}{T_0' } \cdot \int_{0}^{T_0'}\varepsilon(t)^2 \hspace{0.05cm}{\rm d}t \hspace{0.05cm},$$ | :$$P_{\rm Q} = \frac{1}{T_0' } \cdot \int_{0}^{T_0'}\varepsilon(t)^2 \hspace{0.05cm}{\rm d}t \hspace{0.05cm},$$ | ||
− | + | where the time $T_0'$ is to be chosen appropriately. | |
− | + | Quantization SNR is the ratio $\rho_{\rm Q} = {P_{\rm S}}/{P_{\rm Q}}\hspace{0.05cm},$ which is usually given logarithmically (in dB). | |
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− | + | Hints: | |
− | * | + | *The exercise belongs to the chapter [[Modulation_Methods/Pulse_Code_Modulation|Pulse Code Modulation]]. |
− | * | + | *Reference is made in particular to the page [[Modulation_Methods/Pulse_Code_Modulation#Quantization_and_quantization_noise|Quantization and quantization Noise]]. |
− | === | + | ===Questions=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {Calculate the signal power $P_{\rm S}$ (referred to the resistor $1 \ \rm Ω$ ). |
|type="{}"} | |type="{}"} | ||
− | $P_{\rm S} \ = \ $ | + | $P_{\rm S} \ = \ $ { 12 3% } $\ \rm V^2$ |
− | { | + | {Which statements are true for the error signal $ε(t)$ ? |
|type="[]"} | |type="[]"} | ||
− | + $ε(t)$ | + | + $ε(t)$ has a sawtooth shape. |
− | - $ε(t)$ | + | - $ε(t)$ has a step-like progression. |
− | + $ε(t)$ | + | + $ε(t)$ is restricted to the range $±{\it Δ}/2 = ±1 \ \rm V$ . |
− | + $ε(t)$ | + | + $ε(t)$ has period $T_0' = T_0/M$. |
− | { | + | {What is the quantization noise power $P_{\rm Q}$ for $M=6$? |
|type="{}"} | |type="{}"} | ||
− | $P_{\rm Q} \ = \ $ { 0.333 3% | + | $P_{\rm Q} \ = \ $ { 0.333 3% } $\ \rm V^2$ |
− | { | + | {Calculate the quantization noise ratio for $M = 6$. |
|type="{}"} | |type="{}"} | ||
− | $10 | + | $10 - \lg \ ρ_{\rm Q} \ = \ $ { 15.56 3% } $\ \rm dB$ |
− | { | + | {What values result from quantization with $N = 8$ or $N = 16$ bits? |
|type="{}"} | |type="{}"} | ||
− | $N = 8\text{:}\hspace{0.35cm}10 | + | $N = 8\text{:}\hspace{0.35cm}10 ⋅ \lg \ ρ_{\rm Q} \ = \ $ { 48.16 3% } $\ \rm dB$ |
− | $N = 16\text{:}\hspace{0.15cm}10 | + | $N = 16\text{:}\hspace{0.15cm}10 ⋅ \lg \ ρ_{\rm Q} \ = \ ${ 96.32 3% } $\ \rm dB$ |
− | { | + | {What conditions must be met for the derived equation to apply to $ρ_{\rm Q}$ ? |
|type="[]"} | |type="[]"} | ||
− | + | + | + All amplitude values are equally probable. |
− | + | + | + A linear quantizer is present. |
− | + | + | + The quantizer is exactly matched to the signal $(Q_{\rm max} = q_{\rm max})$. |
</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(1)''' | + | '''(1)''' The signal power $P_{\rm S} $ is equal to the root mean square of $q(t)$ if the reference resistance $1 \rm Ω$ is used and therefore the unit $\rm V^2$ is accepted for the power. |
− | * | + | *Due to periodicity and symmetry, averaging over the time domain $T_0/2$ is sufficient: |
− | :$$P_{\rm S} | + | :$$P_{\rm S} = \frac{1}{T_0/2} \cdot \int_{0}^{T_0/2}q^2(t) \hspace{0.05cm}{\rm d}t = \frac{2 \cdot q_{\rm max}^2}{T_0} \cdot \int_{0}^{T_0/2}\left ( { 2 \cdot t}/{T_0} \right )^2 \hspace{0.05cm}{\rm d}t= \frac{2 \cdot q_{\rm max}^2}{T_0} \cdot \frac{T_0}{2} \cdot \int_{0}^{1}x^2 \hspace{0.05cm}{\rm d}x = \frac{q_{\rm max}^2}{3} \hspace{0.05cm}.$$ |
− | * | + | *Here the substitution $x = 2 - t/T_0$ was used. With $q_{\rm max} = 6 \ \rm V$ one gets $P_\rm S\hspace{0.15cm}\underline { = 12 \ V^2}$. |
− | [[File:P_ID1616__Mod_A_4_4.png|right|frame| | + | [[File:P_ID1616__Mod_A_4_4.png|right|frame|error signal for $Q_{\rm max} = q_{\rm max}$]] |
− | '''(2)''' | + | '''(2)''' Correct are <u>suggested solutions 1, 3, and 4</u>: |
− | * | + | *We assume here $Q_{\rm max} = q_{\rm max} = 6 \ \rm V$ . |
− | * | + | *This gives the sawtooth-shaped error signal $ε(t)$ between $±1\ \rm V$. |
− | * | + | *The period duration is $T_0' = T_0/6$. |
− | '''(3)''' | + | '''(3)''' The error signal $ε(t)$ proceeds in the same way as $q(t)$ sawtooth. |
− | * | + | *Thus, the same equation as in subtask '''(1)'''' is suitable for calculating the root mean square. |
− | * | + | *Note, however, that the amplitude is smaller by a factor $M$ while the different period duration does not matter for the averaging: |
:$$P_{\rm Q} = \frac{P_{\rm S}}{M^2} = \frac{12\,{\rm V}^2}{36}\hspace{0.15cm}\underline {= 0.333\,{\rm V}^2 }\hspace{0.05cm}.$$ | :$$P_{\rm Q} = \frac{P_{\rm S}}{M^2} = \frac{12\,{\rm V}^2}{36}\hspace{0.15cm}\underline {= 0.333\,{\rm V}^2 }\hspace{0.05cm}.$$ | ||
− | '''(4)''' | + | '''(4)''' The results of the subtasks '''(1)''' and '''(3)''' lead to the quantization SNR: |
:$$\rho_{\rm Q} = \frac{P_{\rm S}}{P_{\rm Q}} = M^2 = 36 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q}\hspace{0.15cm}\underline { =15.56\,{\rm dB}} \hspace{0.05cm}.$$ | :$$\rho_{\rm Q} = \frac{P_{\rm S}}{P_{\rm Q}} = M^2 = 36 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q}\hspace{0.15cm}\underline { =15.56\,{\rm dB}} \hspace{0.05cm}.$$ | ||
− | '''(5)''' | + | '''(5)''' With $M = 2^N$ we obtain in general: |
− | :$$ \rho_{\rm Q} = M^2 = 2^{2N} \hspace{0.3cm}\ | + | :$$ \rho_{\rm Q} = M^2 = 2^{2N} \hspace{0.3cm}\rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} =20 \cdot {\rm lg}\hspace{0.1cm}(2)\cdot N \approx 6.02\,{\rm dB} \cdot N .$$ |
− | * | + | *This results in the special cases we are looking for: |
:$$N = 8:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline {= 48.16\,{\rm dB}}\hspace{0.05cm},$$ | :$$N = 8:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline {= 48.16\,{\rm dB}}\hspace{0.05cm},$$ | ||
:$$N = 16:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline { = 96.32\,{\rm dB}}\hspace{0.05cm}.$$ | :$$N = 16:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline { = 96.32\,{\rm dB}}\hspace{0.05cm}.$$ | ||
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− | '''(6)''' | + | '''(6)''' <u>All of the above preconditions</u> must be satisfied: |
− | * | + | *For nonlinear quantization, the simple relation $ρ_{\rm Q} = M^2$ does not hold. |
− | * | + | *For an amplitude distribution other than the uniform distribution $ρ_{\rm Q} = M^2$ is also only an approximation, but this is usually accepted. |
− | * | + | *If $Q_{\rm max} < q_{\rm max}$, truncation of the peaks occurs, while with $Q_{\rm max} > q_{\rm max}$ the quantization intervals are larger than required. |
[[File:P_ID1618__Mod_A_4_4f.png|right|frame|Quantisierung mit $Q_{\rm max} \ne q_{\rm max}$]] | [[File:P_ID1618__Mod_A_4_4f.png|right|frame|Quantisierung mit $Q_{\rm max} \ne q_{\rm max}$]] | ||
<br><br><br><br> | <br><br><br><br> | ||
− | + | The graph shows the error signals $ε(t)$ for $Q_{\rm max} > q_{\rm max}$ (left) and $Q_{\rm max} < q_{\rm max}$ (right). | |
− | In | + | In both cases, the quantization noise power is significantly larger than calculated in point '''(3)''' . |
Revision as of 20:11, 19 March 2022
To calculate the quantization noise power $P_{\rm Q}$ we assume a periodic sawtooth-shaped source signal $q(t)$ with value range $±q_{\rm max}$ and period duration $T_0$ .
- In the mean time domain $-T_0/2 ≤ t ≤ T_0/2$ holds: $q(t) = q_{\rm max} \cdot \left ( {2 \cdot t}/{T_0} \right ).$
- We refer to the power of the signal $q(t)$ here as the transmit power $P_{\rm S}$.
The signal $q(t)$ is quantized according to the graph with $M = 6$ stages. The quantized signal is $q_{\rm Q}(t)$, where:
- The linear quantizer is designed for the amplitude range $±Q_{\rm max}$ such that each quantization interval has width ${\it Δ} = 2/M - Q_{\rm max}$ .
- The diagram shows this fact for $Q_{\rm max} = q_{\rm max} = 6 \ \rm V$. These numerical values shall be assumed up to and including the subtask (5) .
The so-called quantization noise power is defined as the root mean square of the difference signal $ε(t) = q_{\rm Q}(t) - q(t)$ . It holds
- $$P_{\rm Q} = \frac{1}{T_0' } \cdot \int_{0}^{T_0'}\varepsilon(t)^2 \hspace{0.05cm}{\rm d}t \hspace{0.05cm},$$
where the time $T_0'$ is to be chosen appropriately.
Quantization SNR is the ratio $\rho_{\rm Q} = {P_{\rm S}}/{P_{\rm Q}}\hspace{0.05cm},$ which is usually given logarithmically (in dB).
Hints:
- The exercise belongs to the chapter Pulse Code Modulation.
- Reference is made in particular to the page Quantization and quantization Noise.
Questions
Solution
- Due to periodicity and symmetry, averaging over the time domain $T_0/2$ is sufficient:
- $$P_{\rm S} = \frac{1}{T_0/2} \cdot \int_{0}^{T_0/2}q^2(t) \hspace{0.05cm}{\rm d}t = \frac{2 \cdot q_{\rm max}^2}{T_0} \cdot \int_{0}^{T_0/2}\left ( { 2 \cdot t}/{T_0} \right )^2 \hspace{0.05cm}{\rm d}t= \frac{2 \cdot q_{\rm max}^2}{T_0} \cdot \frac{T_0}{2} \cdot \int_{0}^{1}x^2 \hspace{0.05cm}{\rm d}x = \frac{q_{\rm max}^2}{3} \hspace{0.05cm}.$$
- Here the substitution $x = 2 - t/T_0$ was used. With $q_{\rm max} = 6 \ \rm V$ one gets $P_\rm S\hspace{0.15cm}\underline { = 12 \ V^2}$.
(2) Correct are suggested solutions 1, 3, and 4:
- We assume here $Q_{\rm max} = q_{\rm max} = 6 \ \rm V$ .
- This gives the sawtooth-shaped error signal $ε(t)$ between $±1\ \rm V$.
- The period duration is $T_0' = T_0/6$.
(3) The error signal $ε(t)$ proceeds in the same way as $q(t)$ sawtooth.
- Thus, the same equation as in subtask (1)' is suitable for calculating the root mean square.
- Note, however, that the amplitude is smaller by a factor $M$ while the different period duration does not matter for the averaging:
- $$P_{\rm Q} = \frac{P_{\rm S}}{M^2} = \frac{12\,{\rm V}^2}{36}\hspace{0.15cm}\underline {= 0.333\,{\rm V}^2 }\hspace{0.05cm}.$$
(4) The results of the subtasks (1) and (3) lead to the quantization SNR:
- $$\rho_{\rm Q} = \frac{P_{\rm S}}{P_{\rm Q}} = M^2 = 36 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q}\hspace{0.15cm}\underline { =15.56\,{\rm dB}} \hspace{0.05cm}.$$
(5) With $M = 2^N$ we obtain in general:
- $$ \rho_{\rm Q} = M^2 = 2^{2N} \hspace{0.3cm}\rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} =20 \cdot {\rm lg}\hspace{0.1cm}(2)\cdot N \approx 6.02\,{\rm dB} \cdot N .$$
- This results in the special cases we are looking for:
- $$N = 8:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline {= 48.16\,{\rm dB}}\hspace{0.05cm},$$
- $$N = 16:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline { = 96.32\,{\rm dB}}\hspace{0.05cm}.$$
(6) All of the above preconditions must be satisfied:
- For nonlinear quantization, the simple relation $ρ_{\rm Q} = M^2$ does not hold.
- For an amplitude distribution other than the uniform distribution $ρ_{\rm Q} = M^2$ is also only an approximation, but this is usually accepted.
- If $Q_{\rm max} < q_{\rm max}$, truncation of the peaks occurs, while with $Q_{\rm max} > q_{\rm max}$ the quantization intervals are larger than required.
The graph shows the error signals $ε(t)$ for $Q_{\rm max} > q_{\rm max}$ (left) and $Q_{\rm max} < q_{\rm max}$ (right).
In both cases, the quantization noise power is significantly larger than calculated in point (3) .