Loading [MathJax]/jax/element/mml/optable/GreekAndCoptic.js

Linear Distortions of Periodic Signals

Aus LNTwww
Wechseln zu:Navigation, Suche

Open Applet in new Tab

Applet Description


This applet illustrates the effects of linear distortions (attenuation distortions and phase distortions) with

Meanings of the used signals
  • the input signal x(t)   ⇒   power Px:
x(t)=x1(t)+x2(t)=A1cos(2πf1tφ1)+A2cos(2πf2tφ2),
  • the output signal y(t)   ⇒   power Py:
y(t)=α1x1(tτ1)+α2x2(tτ2),
  • the matched output signal z(t)   ⇒   power Pz:
z(t)=kMy(tτM)+α2x2(tτ2),
  • the difference signal   ε(t)=z(t)x(t)   ⇒   power Pε.


The next block in the model above is Matching: The output signal y(t) is adjusted in amplitude and phase with equal quantities kM and τM for all frequencies which means that this is not a frequency-dependent equalization. Using the signal z(t), one can differentiate between:

  • attenuation distortion and frequency–independant attenuation, as well as
  • phase distortion and frequency–independant delay.


The Distortion Power PD is used to measure the strength of the linear distortion and is defined as:

PD=minkM, τMPε.

German description


Theoretical Background


Distortions refer to generally unwanted alterations of a message signal through a transmission system. Together with the strong stochastic effects (noise, crosstalk, etc.), they are a crucial limitation for the quality and rate of transmission.

Just as the intensity of noise can be assessed through

  • the Noise Power PN and
  • the Signal–to–Noise Ratio (SNR) ρN,


distortions can be quantified through

  • the Distortion Power PD and
  • the Signal–to–Distortion Ratio (SDR)
ρD=Signal PowerDistortion Power=PxPD.


Linear and Nonlinear Distortions


A distinction is made between linear and nonlinear distortions:

  • Nonlinear distortions occur, if at all times t the nonlinear correlation y=g(x)const.x exists between the signal values x=x(t) at the input and y=y(t) at the output, whereby y=g(x) is defined as the system's nonlinear characteristic. By creating a cosine signal at the input with frequency f0 the output signal includes f0, as well as multiple harmonic waves. We conclude that new frequencies arise through nonlinear distortion.
For clarification of nonlinear distortions
Description of a linear system
  • Linear distortions occur, if the transmission channel is characterized by a frequency response H(f)const. Various frequencies are attenuated and delayed differently. Characteristic of this is that although frequencies can disappear (for example, through a low–pass, a high–pass, or a band–pass), no new frequencies can arise.


In this applet only linear distortions are considered.


Description Forms for the Frequency Response


The generally complex valued frequency response can be represented as follows:

H(f)=|H(f)|ejb(f)=ea(f)ejb(f).

This results in the following description variables:

  • The absolute value |H(f)| is called amplitude response and in logarithmic form attenuation function:
a(f)=ln|H(f)|inNeper(Np)=20lg|H(f)|inDecibel(dB).
  • The phase function b(f) indicates the negative frequency–dependent angle of H(f) in the complex plane based on the real axis:
b(f)=arcH(f)inRadian(rad).


Low–pass of Order N


Attenuation function a(f) and phase function b(f) of a low–Pass of order N

The frequency response of a realizable low–pass (LP) of order N is:

H(f)=[11+jf/f0]N.

For example the RC low–pass is a first order low–pass. Consequently we can obtain

  • the attenuation function:
a(f)=N/2ln[1+(f/f0)2],
  • the phase function:
b(f)=Narctan(f/f0),
  • the attenuation factor for the frequency f=fi:
αi=|H(f=fi)|=[1+(fi/f0)2]N/2
x(t)=Aicos(2πfit)y(t)=αiAicos(2πfit),
  • the phase delay for the frequency f=fi:
τi=b(fi)2πfi=Narctan(fi/f0)2πfi
x(t)=Aicos(2πfit)y(t)=Aicos(2πfi(tτi)).


High–pass of Order N


Attenuation function a(f) and phase function b(f) of a high–pass of order N

The frequency response of a realizable high–pass (HP) of order N is:

H(f)=[jf/f01+jf/f0]N.

For example the LC high pass is a first order high pass. Consequently we can obtain

  • the attenuation function:
a(f)=N/2ln[1+(f0/f)2],
  • the phase function:
b(f)=Narctan(f0/f),
  • the attenuation factor for the frequency f=fi:
αi=|H(f=fi)|=[1+(f0/fi)2]N/2
x(t)=Aicos(2πfit)y(t)=αiAicos(2πfit),
  • the phase delay for the frequency f=fi:
τi=b(fi)2πfi=Narctan(f0/fi)2πfi
x(t)=Aicos(2πfit)y(t)=Aicos(2πfi(tτi)).


Phase function b(f) of high–pass and low–pass

Example:  This graphic shows the phase function b(f) with the cut–off frequency f0=1 kHz and order N=1

  • of a low–pass (green curve),
  • of a high–pass (violet curve).


The input signal is sinusoidal with frequency fS=1.25 kHz whereby this signal is only turned on at t=0:

x(t)={0sin(2πfSt)(t<0),(t>0).

The left graphic shows the signal x(t). The dashed line marks the first zero at t=T0=0.8 ms. The other two graphics show the output signals yLP(t) und yHP(t) of low–pass and high–pass, whereby the change in amplitude was balanced in both cases.

Input signal x(t) (enframed in blue) as well as output signals yLP(t) ⇒   green and yHP(t) ⇒   magenta
  • The first zero of the signal yLP(t) after the low–pass is delayed by τLP=0.9/(2π)T00.115 ms compared to the first zero of x(t)   ⇒   marked with green arrow, whereby bLP(f/fS=0.9 rad) was considered.
  • In contrast, the phase delay of the high–pass is negative: τHP=0.67/(2π)T00.085 ms and therefore the first zero of yHP(t) occurs before the dashed line.
  • Following this transient response, in both cases the zero crossings again come in the raster of the period duration T0=0.8 ms.


Remark: The shown signals were created using the interactive applet Causal systems – Laplace transform.

Attenuation and Phase Distortions


Requirements for a non–distorting channel

The adjacent figure shows

  • the even attenuation function a(f)   ⇒   a(f)=a(f), and
  • the uneven function curve b(f)   ⇒   b(f)=b(f)


of a non–distorting channel. One can see:

  • In a distortion–free system the attenuation function a(f) must be constant betweenfU and fO around the carrier frequency fT, where the input signal exists   ⇒   X(f)0.
  • From the specified constant attenuation value 6 dB follows for the amplitude response |H(f)|=0.5   ⇒   the signal values of all frequencies are thus halved by the system   ⇒   no attenuation distortions.
  • In addition, in such a system, the phase function b(f) between fU and fO must increase linearly with the frequency. As a result, all frequency components are delayed by the same phase delay τ   ⇒   no phase distortion.
  • The delay τ is fixed by the slope of b(f). The phase function b(f) \equiv 0 would result in a delay–less system   ⇒   τ = 0.


The following summary considers that – in this applet – the input signal is always the sum of two harmonic oscillations,

x(t) = x_1(t) + x_2(t) = A_1\cdot \cos\left(2\pi f_1\cdot t- \varphi_1\right)+A_2\cdot \cos\left(2\pi f_2\cdot t- \varphi_2\right),

and therefore the channel influence is fully described by the attenuation factors \alpha_1 and \alpha_2 as well as the phase delays \tau_1 and \tau_2:

y(t) = \alpha_1 \cdot x_1(t-\tau_1) + \alpha_2 \cdot x_2(t-\tau_2).

\text{Summary:} 

  • A signal y(t) is only distortion–free compared to x(t) if \alpha_1 = \alpha_2= \alpha   and   \tau_1 = \tau_2= \tau   ⇒   y(t) = \alpha \cdot x(t-\tau).
  • Attenuation distortions occur when \alpha_1 \ne \alpha_2. If \alpha_1 \ne \alpha_2 and \tau_1 = \tau_2, then there are exclusively attenuation distortions.
  • Phase distortions occur when \tau_1 \ne \tau_2. If \tau_1 \ne \tau_2 and \alpha_1 = \alpha_2, then there are exclusively phase distortions.



Exercises


BlaBla

(1)   We set the parameters for the input signal x(t) to A_1 = 0.8\ {\rm V}, \ A_2 = 0.6\ {\rm V}, \ f_1 = 0.5\ {\rm kHz}, \ f_2 = 1.5\ {\rm kHz}, \ \varphi_1 = 90^\circ, \ \varphi_2 = 30^\circ.

Calculate the signal's cycle duration T_0 and power P_x. Can you read the value for P_x off the applet?


\hspace{1.0cm}\Rightarrow\hspace{0.3cm}T_0 = \big [\hspace{-0.1cm}\text{ greatest common divisor }(0.5 \ {\rm kHz}, \ 1.5 \ {\rm kHz})\big ]^{-1}\hspace{0.15cm}\underline{ = 2.0 \ {\rm ms}};

\hspace{1.85cm} P_x = A_1^2/2 + A_2^2/2 \hspace{0.15cm}\underline{= 0.5 \ {\rm V^2}} = P_\varepsilon\text{, if }\hspace{0.15cm}\underline{k_{\rm M} = 0} \ \Rightarrow \ z(t) \equiv 0.

(2)  Vary \varphi_2 between \pm 180^\circ while assuming the other parameters from Exercise (1). How does the value of T_0 and P_x change?


\hspace{1.0cm}\Rightarrow\hspace{0.3cm}\text{No changes:}\hspace{0.2cm}\hspace{0.15cm}\underline{ T_0 = 2.0 \ {\rm ms}; \hspace{0.2cm} P_x = 0.5 \ {\rm V^2}}.

(3)   Vary f_2 between 0 \le f_2 \le 10\ {\rm kHz} while assuming the other parameters from Exercise (1). How does the value of P_x change?


\hspace{1.0cm}\Rightarrow\hspace{0.3cm}\text{No changes if }f_2 \ne 0\text{ or } f_2 \ne f_1\text{:}\hspace{0.3cm} \hspace{0.15cm}\underline{P_x = 0.5 \ {\rm V^2}}\text{.} \hspace{0.2cm} T_0 \text{ changes if }f_2\text{is not a multiple of }f_1.

\hspace{1.85cm}\text{If }f_2 = 0\text{:}\hspace{0.2cm} P_x = A_1^2/2 + A_2^2\hspace{0.15cm}\underline{ = 0.68 \ {\rm V^2}}. \hspace{3cm}

\hspace{1.85cm}\text{If }f_2 = f_1\text{:}\hspace{0.2cm} P_x = [A_1\cos(\varphi_1) + A_2\cos(\varphi_2)]^2/2 + [A_1\sin(\varphi_1) + A_2\sin(\varphi_2)]^2/2 \text{.}

\hspace{1.85cm}\text{Mit } \varphi_1 = 90^\circ, \ \varphi_2 = 30^\circ\text{:}\hspace{0.3cm}\hspace{0.15cm}\underline{ P_x = 0.74 \ {\rm V^2}}\text{.}

(4)   Going by the previous input signal x(t) we set following parameters to: \alpha_1 = \alpha_2 = 0.5, \ \tau_1 = \tau_2 = 0.5\ {\rm ms}, k_{\rm M} = 1 \text{ and } \tau_{\rm M} = 0 .

Are there linear distortions? Calculate the reception power P_y and the power P_\varepsilon of the differential signal \varepsilon(t) = z(t) - x(t).


\hspace{1.0cm}\Rightarrow \hspace{0.3cm}\hspace{0.15cm}\underline{ y(t) = 0.5 \cdot x(t- 1\ {\rm ms})}\text{ is only attenuated and delayed, but not distorted.}

\hspace{1.85cm}\text{Reception power:}\hspace{0.2cm} P_y = (A_1/2)^2/2 + (A_2/2)^2/2\hspace{0.15cm}\underline{ = 0.125 \ {\rm V^2}}\text{. } P_\varepsilon \text{ is significantly greater:} \hspace{0.1cm} \hspace{0.15cm}\underline{P_\varepsilon = 0.625 \ {\rm V^2}}.

(5)   With otherwise the same settings as in Exercise (4), vary the matching parameters k_{\rm M} \text{ and } \tau_{\rm M}. How big is the distortion power P_{\rm D}?


\hspace{1.0cm}\Rightarrow \hspace{0.3cm} P_{\rm D}\text{is equal to }P_\varepsilon \text{ when using the ideal matching parameters:} \hspace{0.2cm}k_{\rm M} = 2 \text{ und } \tau_{\rm M}=T_0 - 0.5\ {\rm ms} = 1.5\ {\rm ms}

\hspace{1.0cm}\Rightarrow \hspace{0.3cm}z(t) = x(t)\hspace{0.3cm}\Rightarrow \hspace{0.3cm}\varepsilon(t) = 0\hspace{0.3cm}\Rightarrow \hspace{0.3cm}P_{\rm D}\hspace{0.15cm}\underline{ = P_\varepsilon = 0} \hspace{0.3cm}\Rightarrow \hspace{0.3cm}\text{Neither attenuation nor phase distortion.}

(6)   The channel parameters are now set to: \alpha_1 = 0.5, \hspace{0.15cm}\underline{\alpha_2 = 0.2}, \ \tau_1 = \tau_2 = 0.5\ {\rm ms}. Calculate the distortion power P_{\rm D} and the Signal-to-Distortion ratio (\rm SDR) \ \rho_{\rm D}.


\hspace{1.0cm}\Rightarrow \hspace{0.3cm} P_{\rm D} = P_\varepsilon \text{ when using the best matching parameters:} \hspace{0.2cm}\hspace{0.15cm}\underline{k_{\rm M} = 2.24} \text{ und } \hspace{0.15cm}\underline{\tau_{\rm M} = 1.5\ {\rm ms} }\text{:} \hspace{0.2cm}\hspace{0.15cm}\underline{P_{\rm D} = 0.059 \ {\rm V^2}}.

\hspace{1.85cm}\text{Attenuation distortions only.} \hspace{0.3cm}\text{Signal-to-Distortion-Ratio}\ \hspace{0.15cm}\underline{\rho_{\rm D} = P_x/P_\varepsilon \approx 8.5}.

(7)   The channel parameters are now set to: \alpha_1 = \alpha_2 = 0.5, \ \tau_1 \hspace{0.15cm}\underline{= 2\ {\rm ms} }, \ \tau_2 = 0.5\ {\rm ms}. Calculate the distortion power P_{\rm D} and the the Signal-to-Distortion ratio \rho_{\rm D}?


\hspace{1.0cm}\Rightarrow \hspace{0.3cm} P_{\rm D} = P_\varepsilon \text{when using the best matching parameters:} \hspace{0.2cm}\hspace{0.15cm}\underline{k_{\rm M} = 1.84} \text{ and } \tau_{\rm M}\hspace{0.15cm}\underline{ = 0.15\ {\rm ms} }\text{:} \hspace{0.2cm}\hspace{0.15cm}\underline{P_{\rm D} = 0.071 \ {\rm V^2}}.

\hspace{1.85cm}\text{Phase distortions only.} \hspace{0.3cm}\text{Signal-to-Distortion-Ratio}\ \hspace{0.15cm}\underline{\rho_{\rm D} = P_x/P_\varepsilon \approx 7}.

(8)   The channel parameters are now set to: \hspace{0.15cm}\underline{\alpha_1 = 0.5} , \hspace{0.15cm}\underline{\alpha_2 = 0.2} , \ \hspace{0.15cm}\underline{\tau_1= 0.5\ {\rm ms} }, \ \hspace{0.15cm}\underline{\tau_2 = 0.3\ {\rm ms} }. Are there attenuation distortions? Are there phase distortions? How can y(t) be approximated? How can y(t) be approximated? Annotation: \cos(3x) = 4 \cdot \cos(x)^3 - 3\cdot \cos(x).


\hspace{1.0cm}\Rightarrow\hspace{0.3cm} \text{Both attenuation and phase distortions, because }\alpha_1 \ne \alpha_2\text{ and }\tau_1 \ne \tau_2.

\hspace{1.85cm}y(t) = y_1(t) + y_2(t)\ \Rightarrow \ y_1(t) = A_1 \cdot \alpha_1 \cdot \sin[2\pi f_1\ (t- 0.5\ \rm ms)] = -0.4 \ {\rm V} \cdot \cos(2\pi f_1 t)

\hspace{1.85cm} y_2(t) = \alpha_2 \cdot x_2(t- \tau_2) \text{ mit }x_2(t) = A_2 \cdot \cos[2\pi f_2\ (t- 30^\circ)] \approx A_2 \cdot \cos[2\pi f_2\ (t- 1/36 \ \rm ms)]

\hspace{1.85cm} \Rightarrow \ y_2(t) = 0.12 \ {\rm V} \cdot \cos[2\pi f_2\ (t- 0.328 \ {\rm ms})] \approx -0.12 \ { \rm V} \cdot \cos[2\pi f_2t] .

\hspace{1.85cm} \Rightarrow \ y(t) = y_1(t) + y_2(t) \approx -0.4 \ {\rm V} \cdot [\cos(2\pi \cdot f_1\cdot t) + 1/3 \cdot \cos(2\pi \cdot 3 f_1 \cdot t) = -0.533 \ {\rm V} \cdot \cos^3(2\pi f_1 t).

(9)   Assuming the parameters from Exercize (8). Calculate the distortion power P_{\rm D} and the the Signal-to-Distortion ratio \rho_{\rm D}?


\hspace{1.0cm}\text{Best possible adaptation:} \hspace{0.2cm}\hspace{0.15cm}\underline{k_{\rm M} = 1.96} \text{, } \hspace{0.15cm}\underline{\tau_{\rm M} = 1.65\ {\rm ms} }\text{:} \hspace{0.2cm}\hspace{0.15cm}\underline{P_{\rm D} = 0.15 \ {\rm V^2} },\hspace{0.1cm}\hspace{0.15cm}\underline{\rho_{\rm D} = 0.500/0.156 \approx 3.3}.

(10)  Now we set A_2 = 0 and A_1 = 1\ {\rm V}, \ f_1 = 1\ {\rm kHz}, \ \varphi_1 = 0^\circ. The channel is a Low-pass of order 1 \underline{(f_0 = 1\ {\rm kHz})}.
Are there any attenuation or phase distortions? Calculate the channel coefficients \alpha_1 and \tau_1


\hspace{1.0cm}\text{At only one frequency there are neither attenuation nor phase distortions.} \hspace{1.0cm}\text{Attenuation factor for }f_1=f_0\text{ and }N=1\text{: }\alpha_1 =|H(f = f_1)| = [1+( f_1/f_0)^2]^{-N/2} = 2^{-1/2}= 1/\sqrt{2}\hspace{0.15cm}\underline{=0.707}, \hspace{1.0cm}\text{Phase factor for }f_1=f_0\text{ and }N=1\text{: }\tau_1 = N \cdot \arctan( f_1/f_0)/(2 \pi f_i)=\arctan( 1)/(2 \pi f_i) =1/(8f_1) \hspace{0.15cm}\underline{=0.125 \ \rm ms}.

(11)   How do the channel parameters change when using a Low-pass of order 2 compared to a Low-pass of order 1 (f_0 = 1\ {\rm kHz})?


\hspace{1.0cm}\alpha_1 = 0.707^2 = 0.5 and \tau_1 = 2 \cdot 0.125 0.25 \ {\rm ms}.

\hspace{1.0cm}\text{The signal }y(t)\text{ is only half as big as }x(t)\text{ and follows it: The cosine turns into a sine function}.

(12)   What differences arise when using a High-pass of order 2 compared to a Low-pass of order 2 (f_0 = 1\ {\rm kHz})?


\hspace{1.0cm}\text{Since }f_1 = f_0\text{ the attenuation factor }\alpha_1 = 0.5\text{ stays the same and }\tau_1 = -0.25 \ {\rm ms}\text{ which means:}

\hspace{1.0cm}\text{The signal }y(t)\text{ is also only half as big as }x(t)\text{ and precedes it: The cosine turns into the Minus–sine function}.

(13)   What differences at the signal y(t) can be observed between the Low-pass and the High-pass of order 2 (f_0 = 1\ {\rm kHz}) when you start with the initial input signal according to Exercise (1) and continuously raise f_2 up to 10 \ \rm kHz ?


\hspace{1.0cm}\text{With the Low-pass the second portion is increasingly suppressed. For }f_2 = 10 \ {\rm kHz}\text{ : }y_{\rm HP}(t) \approx 0.2 \cdot x_1(t-0.3 \ \rm ms).

\hspace{1.0cm}\text{With the High-pass however the second portion overweighs. For }f_2 = 10 \ {\rm kHz}\text{ : }y_{\rm TP}(t) \approx 0.8 \cdot x_1(t+0.7 \ \rm ms) + x_2(t).

Instruction Sheet

Periodendauer fertig version1.png

    (A)     Parametereingabe per Slider

    (B)     Bereich der graphischen Darstellung

    (C)     Variationsmöglichkeit für die graphische Darstellung

    (D)     Abspeichern und Zurückholen von Parametersätzen

    (E)     Numerikausgabe des Hauptergebnisses T_0; graphische Verdeutlichung durch rote Linie

    (F)     Ausgabe von x_{\rm max} und der Signalwerte x(t_*) = x(t_* + T_0)= x(t_* + 2T_0)

    (G)     Darstellung der Signalwerte x(t_*) = x(t_* + T_0)= x(t_* + 2T_0) durch grüne Punkte

    (H)     Einstellung der Zeit t_* für die Signalwerte x(t_*) = x(t_* + T_0)= x(t_* + 2T_0)

Details zum obigen Punkt (C)

    (*)   Zoom–Funktionen „+” (Vergrößern), „-” (Verkleinern) und \rm o (Zurücksetzen)

    (*)   Verschieben mit „\leftarrow” (Ausschnitt nach links, Ordinate nach rechts), „\uparrow” „\downarrow” und „\rightarrow

Andere Möglichkeiten:

    (*)   Gedrückte Shifttaste und Scrollen: Zoomen im Koordinatensystem,

    (*)   Gedrückte Shifttaste und linke Maustaste: Verschieben des Koordinatensystems.


About the Authors

Dieses interaktive Berechnungstool wurde am Lehrstuhl für Nachrichtentechnik der Technischen Universität München konzipiert und realisiert.

  • Die erste Version wurde 2005 von Bettina Hirner im Rahmen ihrer Diplomarbeit mit „FlashMX–Actionscript” erstellt (Betreuer: Günter Söder ).
  • 2018 wurde dieses Programm von Jimmy He im Rahmen seiner Bachelorarbeit (Betreuer: Tasnád Kernetzky) auf „HTML5” umgesetzt und neu gestaltet.

Once more: Open Applet in new Tab

Open Applet in new Tab