Difference between revisions of "Aufgaben:Exercise 4.2Z: About the Sampling Theorem"
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− | {{quiz-Header|Buchseite= | + | {{quiz-Header|Buchseite=Modulation_Methods/Pulse_Code_Modulation |
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− | [[File:P_ID1610__Mod_Z_4_2.png|right|]] | + | [[File:P_ID1610__Mod_Z_4_2.png|right|frame|Harmonic oscillations of different phase]] |
− | + | The [[Signal_Representation/Discrete-Time_Signal_Representation#Sampling_theorem|sampling theorem]] states that the sampling frequency $f_{\rm A} = 1/T_{\rm A}$ must be at least twice as large as the largest frequency $f_\text {N, max} contained in the source signal q(t)$: | |
− | fA≥2⋅fN,max⇒TA≤12⋅fN,max. | + | :fA≥2⋅fN,max⇒TA≤12⋅fN,max. |
− | + | If this condition is met, then at the receiver the message signal can be passed through a rectangular (ideal) low-pass filter with frequency response | |
− | H(f)={11/20f¨urf¨urf¨ur|f|<fG,|f|=fG,|f|>fG | + | :H(f)={11/20f¨urf¨urf¨ur|f|<fG,|f|=fG,|f|>fG |
− | + | can be completely reconstructed, that is, it is then $v(t) = q(t)$. | |
+ | *The cutoff frequency $f_{\rm G}$ is to be chosen equal to half the sampling frequency. | ||
+ | *The equal sign is generally valid only if the spectrum Q(f) does not contain a discrete spectral line at frequency $f_\text {N, max}$. | ||
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− | + | In this exercise, three different source signals are considered, each of which can be expressed as a harmonic oscillation | |
+ | :q(t) = A \cdot \cos (2 \pi \cdot f_{\rm N} \cdot t - \varphi) | ||
+ | with amplitude A = 1\ \rm V and frequency f_{\rm N}= 5 \ \rm kHz. For the spectral function Q(f) of all represented time signals generally holds: | ||
+ | :$$Q(f) = \frac{A}{2} \cdot \delta (f- f_{\rm N}) \cdot {\rm e}^{-{\rm j}\hspace{0.04cm}\cdot \hspace{0.04cm}\varphi}+ \frac{A}{2} \cdot \delta (f+ f_{\rm N}) \cdot {\rm e}^{+{\rm j}\hspace{0.04cm}\cdot \hspace{0.04cm}\varphi}\hspace{0.05cm}.$$ | ||
+ | The oscillations sketched in the graph differ only by the phase φ: | ||
+ | * φ_1 = 0 ⇒ cosine signal q_1(t), | ||
+ | * $φ_2 = π/2 \ (= 90^\circ)$ ⇒ sinusoidal signal $q_2(t)$, | ||
+ | * $φ_3 = π/4 \ (= 45^\circ)$ ⇒ signal $q_3(t)$. | ||
− | === | + | |
+ | |||
+ | |||
+ | |||
+ | |||
+ | 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#Sampling_and_signal_reconstruction|"Sampling and Signal Reconstruction"]]. | ||
+ | *The sampled source signal is denoted by q_{\rm A}(t) and its spectral function by Q_{\rm A}(f). | ||
+ | *Sampling is always performed at ν \cdot T_{\rm A}. | ||
+ | |||
+ | |||
+ | ===Questions=== | ||
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {Which statements are valid with $f_{\rm A} = 11\ \rm kHz$? |
|type="[]"} | |type="[]"} | ||
− | + | + | + The sampling theorem is always satisfied. |
− | + | + | + All signals can be reconstructed by a low-pass filter. |
− | + | + | + It is always true: $Q_{\rm A}(f = 5 \ {\rm kHz}) = Q(f = 5 \ \rm kHz)$. |
− | { | + | {What sampling distance results with $f_{\rm A} = 10\ \rm kHz$? |
|type="{}"} | |type="{}"} | ||
− | $ | + | $T_{\rm A} \ = \ { 0.1 3% } \ \rm ms$ |
− | { | + | {Which statements are valid for the signal q_1(t) and $f_{\rm A} = 10\ \rm kHz$? |
|type="[]"} | |type="[]"} | ||
− | - | + | - It holds $Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_1(f = 5 \ \rm kHz)$. |
− | + | + | + A complete signal reconstruction is possible ⇒ $v_1(t) = q_1(t)$. |
− | - | + | - The reconstructed signal is $v_1(t) \equiv 0$. |
− | { | + | {What statements hold for the signal q_2(t) and $f_{\rm A} = 10\ \rm kHz$? |
|type="[]"} | |type="[]"} | ||
− | - | + | - It holds $Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_2(f = 5 \ \rm kHz)$. |
− | - | + | - A complete signal reconstruction is possible ⇒ $v_2(t) = q_2(t)$. |
− | + | + | + The reconstructed signal is $v_2(t) \equiv 0$. |
− | { | + | {What statements hold for the signal q_3(t) and $f_{\rm A} = 10\ \rm kHz$? |
|type="[]"} | |type="[]"} | ||
− | - | + | - It holds $Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_3(f = 5 \ \rm kHz)$. |
− | - | + | - A complete signal reconstruction is possible ⇒ $v_3(t) = q_3(t)$. |
− | - | + | - The reconstructed signal is $v_3(t) \equiv 0$. |
</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''1 | + | '''(1)''' <u>All statements</u> are true: |
− | [[File:P_ID1611__Mod_Z_4_2a.png|P_ID1611__Mod_Z_4_2a.png]] | + | [[File:P_ID1611__Mod_Z_4_2a.png|P_ID1611__Mod_Z_4_2a.png|right|frame|Spectral function of the sampled signal]] |
− | + | *The sampling theorem is satisfied by $f_{\rm A} = 11 \ \rm kHz > 2 \cdot 5 \ \rm kHz$ so that a complete signal reconstruction is always possible. | |
− | + | *The spectrum $Q_{\rm A}(f)$ results from $Q(f)$ by periodic continuation at the respective frequency spacing $f_{\rm A}$, which is generally illustrated in the graph. | |
− | + | *By a rectangular low-pass with $f_{\rm G} = f_{\rm A}/2 = 5.5 \ \rm kHz$ the original spectrum Q(f) is obtained. | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | The shift by | |
+ | * $f_{\rm A} = 11 \ \rm kHz$ yields the lines at $+6 \ \rm kHz$ and $+16 \ \rm kHz$, | ||
+ | * $-f_{\rm A} = -11 \ \rm kHz$ yields the lines at $-6 \ \rm kHz$ and $-16 \ \rm kHz$, | ||
+ | * $2 - f_{\rm A} = 22 \ \rm kHz$ yields the lines at $+17 \ \rm kHz$ and $+27 \ \rm kHz$, | ||
+ | * $-2 - f_{\rm A}= -22 \ \rm kHz$ yields the lines at $-17 \ \rm kHz$, $-27 \ \rm kHz$. | ||
− | |||
− | + | '''(2)''' The sampling distance is equal to the reciprocal of the sampling frequency: | |
+ | :$$ T_{\rm A} = {1}/{f_{\rm A} }\hspace{0.15cm}\underline { = 0.1\,{\rm ms}} \hspace{0.05cm}.$$ | ||
− | |||
+ | '''(3)''' The correct solution is <u>suggestion 2</u>: | ||
+ | [[File:P_ID1612__Mod_Z_4_2c.png|P_ID1612__Mod_Z_4_2c.png|right|frame|Spectral function of the sampled cosine signal]] | ||
− | [[File:P_ID1613__Mod_Z_4_2d.png|P_ID1613__Mod_Z_4_2d.png]] | + | *For the cosinusoidal signal, according to this graph with f_{\rm A} = 10 \rm \ kHz: All spectral lines of Q_{\rm A}(f): are real. |
+ | *The periodization of Q(f) with f_{\rm A} = 10 \rm \ kHz leads to a Dirac comb with spectral lines at ±f_{\rm N}, ±f_{\rm N}± f_{\rm A}, ±f_{\rm N}± 2f_{\rm A}, . .. | ||
+ | *Through the superpositions, all Dirac functions have weight A, while the spectral lines of Q(f) are weighted only by A/2 each. | ||
+ | *Because H(f = f_{\rm N}) = H(f = f_{\rm G}) = 0.5 the spectrum V_1(f) after the low-pass is identical to Q_1(f) ⇒ v_1(t) = q_1(t). | ||
+ | *In the time domain, the signal reconstruction can be thought of as follows: The samples of q_1(t) lie exactly at the signal maxima and minima. | ||
+ | *The lowpass filter forms the cosine signal with correct amplitude, frequency and phase. | ||
+ | <br clear=all> | ||
+ | [[File:P_ID1613__Mod_Z_4_2d.png|P_ID1613__Mod_Z_4_2d.png|right|frame|Sampled sine signal]] | ||
+ | '''(4)''' Correct is <u>suggested solution 2</u>: | ||
+ | *All sampled values of q_2(t) now lie exactly at the zero crossings of the sinusoidal signal, which means that here q_{\rm A}(t) \equiv 0 holds. However, this naturally also gives v_2(t) \equiv 0. | ||
+ | *In the spectral domain, the result can be derived using the graph for subtask '''(1)'''. <br>⇒ Q(f) is purely imaginary and the imaginary parts at ±f_{\rm N} have different signs. | ||
+ | *Thus, one positive and one negative part cancel each other in periodization <br>⇒ Q_{\rm A}(f) \equiv 0 ⇒ V_2(f) \equiv 0. | ||
+ | <br clear=all> | ||
+ | [[File:P_ID1614__Mod_Z_4_2e.png|P_ID1614__Mod_Z_4_2e.png|right|frame|Sampled harmonic oscillation with phase φ_3 = π/4]] | ||
+ | '''(5)''' <u>None of the given solutions</u> is correct: | ||
+ | *If in the graph for the subtask '''(1)''' the sampling frequency f_{\rm A} = 11 \ \rm kHz is replaced by f_{\rm A} = 10 \ \rm kHz, the real parts add up, but the imaginary parts cancel out. | ||
+ | *This means that now Q_{\rm A}(f) and V_3(f) are real spectra. This further means: | ||
+ | *The phase information is lost (φ = 0) and the output signal v_3(t) is a cosine signal. | ||
+ | *q_3(t) and v_3(t) thus differ in both amplitude and phase. Only the frequency remains the same. | ||
− | |||
+ | The graph shows | ||
+ | *turquoise the signal q_3(t) and its samples (circles), and | ||
+ | *red dashed the output signal v_3(t) of the low-pass. | ||
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− | + | You can see that the low-pass gives exactly the result you would probably choose if you were to draw a curve through the samples (circles). | |
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− | [[Category: | + | [[Category:Modulation Methods: Exercises|^4.1 Pulse Code Modulation^]] |
Latest revision as of 12:28, 8 April 2022
The sampling theorem states that the sampling frequency f_{\rm A} = 1/T_{\rm A} must be at least twice as large as the largest frequency f_\text {N, max} contained in the source signal q(t):
- f_{\rm A} \ge 2 \cdot f_{\rm N,\hspace{0.05cm}max}\hspace{0.3cm}\Rightarrow \hspace{0.3cm} T_{\rm A} \le \frac{1}{2 \cdot f_{\rm N, \hspace{0.05cm}max}}\hspace{0.05cm}.
If this condition is met, then at the receiver the message signal can be passed through a rectangular (ideal) low-pass filter with frequency response
- H(f) = \left\{ \begin{array}{l} 1 \\ 1/2 \\ 0 \\ \end{array} \right.\quad \begin{array}{*{5}c}{\rm{f\ddot{u}r}} \\{\rm{f\ddot{u}r}} \\{\rm{f\ddot{u}r}} \\ \end{array}\begin{array}{*{10}c} {\hspace{0.04cm}\left| \hspace{0.005cm} f\hspace{0.05cm} \right| < f_{\rm G},} \\ {\hspace{0.04cm}\left| \hspace{0.005cm} f\hspace{0.05cm} \right| = f_{\rm G},} \\ {\hspace{0.04cm}\left| \hspace{0.005cm} f\hspace{0.05cm} \right| > f_{\rm G}} \\ \end{array}
can be completely reconstructed, that is, it is then v(t) = q(t).
- The cutoff frequency f_{\rm G} is to be chosen equal to half the sampling frequency.
- The equal sign is generally valid only if the spectrum Q(f) does not contain a discrete spectral line at frequency f_\text {N, max}.
In this exercise, three different source signals are considered, each of which can be expressed as a harmonic oscillation
- q(t) = A \cdot \cos (2 \pi \cdot f_{\rm N} \cdot t - \varphi)
with amplitude A = 1\ \rm V and frequency f_{\rm N}= 5 \ \rm kHz. For the spectral function Q(f) of all represented time signals generally holds:
- Q(f) = \frac{A}{2} \cdot \delta (f- f_{\rm N}) \cdot {\rm e}^{-{\rm j}\hspace{0.04cm}\cdot \hspace{0.04cm}\varphi}+ \frac{A}{2} \cdot \delta (f+ f_{\rm N}) \cdot {\rm e}^{+{\rm j}\hspace{0.04cm}\cdot \hspace{0.04cm}\varphi}\hspace{0.05cm}.
The oscillations sketched in the graph differ only by the phase φ:
- φ_1 = 0 ⇒ cosine signal q_1(t),
- φ_2 = π/2 \ (= 90^\circ) ⇒ sinusoidal signal q_2(t),
- φ_3 = π/4 \ (= 45^\circ) ⇒ signal q_3(t).
Hints:
- The exercise belongs to the chapter "Pulse Code Modulation".
- Reference is made in particular to the page "Sampling and Signal Reconstruction".
- The sampled source signal is denoted by q_{\rm A}(t) and its spectral function by Q_{\rm A}(f).
- Sampling is always performed at ν \cdot T_{\rm A}.
Questions
Solution
- The sampling theorem is satisfied by f_{\rm A} = 11 \ \rm kHz > 2 \cdot 5 \ \rm kHz so that a complete signal reconstruction is always possible.
- The spectrum Q_{\rm A}(f) results from Q(f) by periodic continuation at the respective frequency spacing f_{\rm A}, which is generally illustrated in the graph.
- By a rectangular low-pass with f_{\rm G} = f_{\rm A}/2 = 5.5 \ \rm kHz the original spectrum Q(f) is obtained.
The shift by
- f_{\rm A} = 11 \ \rm kHz yields the lines at +6 \ \rm kHz and +16 \ \rm kHz,
- -f_{\rm A} = -11 \ \rm kHz yields the lines at -6 \ \rm kHz and -16 \ \rm kHz,
- 2 - f_{\rm A} = 22 \ \rm kHz yields the lines at +17 \ \rm kHz and +27 \ \rm kHz,
- -2 - f_{\rm A}= -22 \ \rm kHz yields the lines at -17 \ \rm kHz, -27 \ \rm kHz.
(2) The sampling distance is equal to the reciprocal of the sampling frequency:
- T_{\rm A} = {1}/{f_{\rm A} }\hspace{0.15cm}\underline { = 0.1\,{\rm ms}} \hspace{0.05cm}.
(3) The correct solution is suggestion 2:
- For the cosinusoidal signal, according to this graph with f_{\rm A} = 10 \rm \ kHz: All spectral lines of Q_{\rm A}(f): are real.
- The periodization of Q(f) with f_{\rm A} = 10 \rm \ kHz leads to a Dirac comb with spectral lines at ±f_{\rm N}, ±f_{\rm N}± f_{\rm A}, ±f_{\rm N}± 2f_{\rm A}, . ..
- Through the superpositions, all Dirac functions have weight A, while the spectral lines of Q(f) are weighted only by A/2 each.
- Because H(f = f_{\rm N}) = H(f = f_{\rm G}) = 0.5 the spectrum V_1(f) after the low-pass is identical to Q_1(f) ⇒ v_1(t) = q_1(t).
- In the time domain, the signal reconstruction can be thought of as follows: The samples of q_1(t) lie exactly at the signal maxima and minima.
- The lowpass filter forms the cosine signal with correct amplitude, frequency and phase.
(4) Correct is suggested solution 2:
- All sampled values of q_2(t) now lie exactly at the zero crossings of the sinusoidal signal, which means that here q_{\rm A}(t) \equiv 0 holds. However, this naturally also gives v_2(t) \equiv 0.
- In the spectral domain, the result can be derived using the graph for subtask (1).
⇒ Q(f) is purely imaginary and the imaginary parts at ±f_{\rm N} have different signs. - Thus, one positive and one negative part cancel each other in periodization
⇒ Q_{\rm A}(f) \equiv 0 ⇒ V_2(f) \equiv 0.
(5) None of the given solutions is correct:
- If in the graph for the subtask (1) the sampling frequency f_{\rm A} = 11 \ \rm kHz is replaced by f_{\rm A} = 10 \ \rm kHz, the real parts add up, but the imaginary parts cancel out.
- This means that now Q_{\rm A}(f) and V_3(f) are real spectra. This further means:
- The phase information is lost (φ = 0) and the output signal v_3(t) is a cosine signal.
- q_3(t) and v_3(t) thus differ in both amplitude and phase. Only the frequency remains the same.
The graph shows
- turquoise the signal q_3(t) and its samples (circles), and
- red dashed the output signal v_3(t) of the low-pass.
You can see that the low-pass gives exactly the result you would probably choose if you were to draw a curve through the samples (circles).