Aufgaben:Exercise 1.4: Rayleigh PDF and Jakes PDS: Difference between revisions

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'''(1)'''  The maximum value of the PDF for both channels is $0.6$ and occurs at $a = 1$.  
'''(1)'''  The maximum value of the PDF for both channels is $0.6$ and occurs at $a = 1$.  
*The Rayleigh–WDF and its derivation are general
*The Rayleigh PDF and its derivative are
:$$f_a(a) \hspace{-0.1cm} = \hspace{-0.1cm} \frac{a}{\sigma^2} \cdot {\rm e}^{ -a^2/(2\sigma^2)} \hspace{0.05cm},$$
:$$f_a(a) \hspace{-0.1cm} = \hspace{-0.1cm} \frac{a}{\sigma^2} \cdot {\rm e}^{ -a^2/(2\sigma^2)} \hspace{0.05cm},$$
$$\frac{\rm d}f_a(a)}{\rm d}a \hspace{-0.1cm} = \hspace{-0.1cm} \frac{1}{\sigma^2} \cdot {\rm e}^{ -a^2/(2\sigma^2)}-
:$$\frac{{\rm d}f_a(a)}{{\rm d}a} \hspace{-0.1cm} = \hspace{-0.1cm} \frac{1}{\sigma^2} \cdot {\rm e}^{ -a^2/(2\sigma^2)}-
  \frac{a^2}{\sigma^4} \cdot {\rm e}^{ -a^2/(2\sigma^2)} \hspace{0.05cm}.$$
  \frac{a^2}{\sigma^4} \cdot {\rm e}^{ -a^2/(2\sigma^2)} \hspace{0.05cm}.$$


*By zeroing the derivative, you can show that the WDF–maximum occurs at $a = \sigma$. Since the Rayleigh–WDF applies to both channels, it follows that
*By setting the derivative to $0$, you can show that the maximum of the PDF occurs at $a = \sigma$. Since the Rayleigh PDF applies to both channels, it follows that
$$\sigma_{\rm R} = \sigma_{\rm B} \hspace{0.15cm} \underline{ = 1} \hspace{0.05cm}.$$
$$\sigma_{\rm R} = \sigma_{\rm B} \hspace{0.15cm} \underline{ = 1} \hspace{0.05cm}.$$




'''(2)'''  Because of the same WDF, the searched probability is also the same for both channels.  
'''(2)'''  As they fading coefficients have the same PDF, the desired probability is also the same for both channels.  
*With the given equation you get for this
*Using the given equation, we have
$${\rm Pr}(a \le 0.316) = {\rm Pr}(20 \cdot {\rm lg}\hspace{0.15cm} a \le -10\,\,{\rm dB}) = 1 - {\rm e}^{ -{0.316^2}/(2\sigma^2)}
$${\rm Pr}(a \le 0.316) = {\rm Pr}(20 \cdot {\rm lg}\hspace{0.15cm} a \le -10\,\,{\rm dB}) = 1 - {\rm e}^{ -{0.316^2}/(2\sigma^2)}
  = 1- 0.951 \hspace{0.15cm} \underline{ \approx 4.9 \%}  
  = 1- 0.951 \hspace{0.15cm} \underline{ \approx 4.9 \%}  
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'''(3)'''&nbsp; <u>The correct solutions are 2, 3 and 6</u>:
'''(3)'''&nbsp; <u>The correct solutions are 2, 3 and 6</u>:
* The smaller speed $v_{\rm B}$ can be recognized by the fact that the amount $|z(t)|$ changes more slowly with the blue curve.
* The smaller speed $v_{\rm B}$ can be recognized by the fact that the magnitude $|z(t)|$ changes more slowly with the blue curve.
* With the vehicle stationary, the LDS degenerates to ${\it \Phi_z}(f_{\rm D}) = 2\sigma^2\cdot \delta(f_{\rm D})$, and it is $|z(t)| = A = \rm const.$, where the constant $A$ is diced according to the Rayleigh distribution.
* When the vehicle is stationary, the PSD degenerates to ${\it \Phi_z}(f_{\rm D}) = 2\sigma^2\cdot \delta(f_{\rm D})$, and we have $|z(t)| = A = \rm const.$, where the constant $A$ is drawn from the Rayleigh distribution.
* At extremely high speed, the Jakes&ndash;spectrum becomes flat and lower over an increasingly wide range. It then approaches the LDS of white noise. However, $v$ would have to be in the order of the speed of light.
* At extremely high speed, the Jakes spectrum becomes flat and has an increasingly smaller magnitude over an increasingly wide range. It then approaches the PSD of white noise. However, $v$ would have to be in the order of the speed of light.




'''(4)'''&nbsp; Correct are the <u>statements 2 and 3</u>:  
'''(4)'''&nbsp; <u>Statements 2 and 3</u> are correct:  
*The Rayleigh&ndash;parameter $\sigma = 1$ also determines the &bdquo;power&rdquo; ${\rm E}[|z(t)|^2] = 2\sigma^2 = 2$ of the random process.  
*The Rayleigh parameter $\sigma = 1$ also determines the &bdquo;power&rdquo; ${\rm E}[|z(t)|^2] = 2\sigma^2 = 2$ of the random process.  
*This applies to both '''R''' and '''B''':
*This applies to both '''R''' and '''B''':
$$\varphi_z ({\rm \delta}t = 0) = 2 \hspace{0.05cm}, \hspace{0.2cm} \int_{-\infty}^{+\infty}{\it \Phi}_z(f_{\rm D}) \hspace{0.15cm}{\rm d}f_{\rm D} = 2 \hspace{0.05cm}.$$
$$\varphi_z ({\rm \delta}t = 0) = 2 \hspace{0.05cm}, \hspace{0.2cm} \int_{-\infty}^{+\infty}{\it \Phi}_z(f_{\rm D}) \hspace{0.15cm}{\rm d}f_{\rm D} = 2 \hspace{0.05cm}.$$

Revision as of 19:46, 25 March 2020

$  bei Rayleigh-Fading mit Dopplereinfluss

We consider two different mobile radio channels with  Rayleigh fading. In both cases the PDF of the magnitude  $a(t) = |z(t)| ≥ 0$  is $$f_a(a) = \frac{a}{\sigma^2} \cdot {\rm e}^{ -{a^2}/(2\sigma^2)}

\hspace{0.05cm}.$$

The probability that this amount is not greater than a given value  $A$  is $${\rm Pr}(|z(t)| \le A) = 1 - {\rm e}^{ -{A^2}/(2\sigma^2)}

\hspace{0.05cm}.$$

The two channels, which are designated according to the colors „Red” and „Blue” in the graphs with  $\rm R$  and  $\rm B$  respectively, differ in the speed  $v$  and thus in the form of the power spectral density (PSD)   ${\it \Phi}_z(f_{\rm D})$.

  • For a Doppler frequency  $f_{\rm D}$  with  $|f_{\rm D}| <f_{\rm D,\hspace{0.05cm}max}$  the Jakes spectrum is given by

$${\it \pi}_z(f_{\rm D}) = \frac{1}{\pi \hspace{-0.05cm}\cdot \hspace{-0.05cm}f_{\rm D, \hspace{0.05cm} max} \hspace{-0.05cm}\cdot \hspace{-0.05cm}\sqrt{ 1 \hspace{-0.05cm}- \hspace{-0.05cm}(f_{\rm D}/f_{\rm D, \hspace{0.05cm} max})^2} }

\hspace{0.05cm}.$$
  • For Doppler frequencies outside this interval from  $-f_{\rm D,\hspace{0.05cm}max}$  to  $+f_{\rm D,\hspace{0.05cm}max}$,   we have ${\it \pi}_z(f_{\rm D})=0$.


The corresponding descriptor in the time domain is the autocorrelation function (ACF): $$\varphi_z ({\rm \delta}t) = 2 \sigma^2 \cdot {\rm J_0}(2\pi \cdot f_{\rm D, \hspace{0.05cm} max} \cdot {\rm \delta}t)\hspace{0.05cm}.$$

  • Here,  ${\rm J_0}(.)$  is the Bessel function of the first kind and zeroth order. We have   ${\rm J_0}(0) = 1$.
  • The maximum Doppler frequency of the channel model  $\rm R$ : is known to be   $f_{\rm D,\hspace{0.05cm}max} = 200 \ \rm Hz$.
  • It is also known that the speeds  $v_{\rm R}$  and  $v_{\rm B}$  differ by the factor  $2$ .
  • Whether  $v_{\rm R}$  is twice as large as  $v_{\rm B}$  or vice versa, you should decide based on the above graphs.




Notes:




Questionnaire

1 Determine the Rayleigh parameter  $\sigma$  for the channels  $\rm R$  and  $\rm B$.

$\sigma_{\rm R} \ = \ $ $\ \ \rm $
$\sigma_{\rm B} \ = \ $ $\ \ \rm $

2 In each case, give the probability that  $20 \cdot {\rm lg} \ a ≤ –10 \ \ \ \rm dB$  which is also  $a ≤ 0.316$  at the same time.

Channel  ${\rm R}\text{:} \hspace{0.4cm} {\rm Pr}(a ≤ 0.316) \ = \ $ $\ \rm \%$
Channel  ${\rm B}\text{:} \hspace{0.4cm} {\rm Pr}(a ≤ 0.316) \ = \ $ $\ \rm \%$

3 Which statements are correct regarding the driving speeds  $v$ ?

$v_{\rm B}$  is twice as big as  $v_{\rm R}$.
$v_{\rm B}$  is half as big as  $v_{\rm R}$.
With  $v = 0$,   $|z(t)|$  would be constant.
With  $v = 0$   $|z(t)|$  would have a white spectrum.
With  $v → ∞$   $|z(t)|$  would be constant.
With  $v → ∞$   $|z(t)|$  would be white.

4 Which of the following statements are correct?

The PSD value  ${\it \Phi_z}(f_{\rm D} = 0)$  is the same for both channels.
The ACF value  $\varphi_z(\Delta t = 0)$  is the same for both channels.
The area under  ${\it \Phi_z}(f_{\rm D})$  is the same for both channels.
The area below  $\varphi_z(\Delta t)$  is the same for both channels.


Sample solution

(1)  The maximum value of the PDF for both channels is $0.6$ and occurs at $a = 1$.

  • The Rayleigh PDF and its derivative are
$$f_a(a) \hspace{-0.1cm} = \hspace{-0.1cm} \frac{a}{\sigma^2} \cdot {\rm e}^{ -a^2/(2\sigma^2)} \hspace{0.05cm},$$
$$\frac{{\rm d}f_a(a)}{{\rm d}a} \hspace{-0.1cm} = \hspace{-0.1cm} \frac{1}{\sigma^2} \cdot {\rm e}^{ -a^2/(2\sigma^2)}-
\frac{a^2}{\sigma^4} \cdot {\rm e}^{ -a^2/(2\sigma^2)} \hspace{0.05cm}.$$
  • By setting the derivative to $0$, you can show that the maximum of the PDF occurs at $a = \sigma$. Since the Rayleigh PDF applies to both channels, it follows that

$$\sigma_{\rm R} = \sigma_{\rm B} \hspace{0.15cm} \underline{ = 1} \hspace{0.05cm}.$$


(2)  As they fading coefficients have the same PDF, the desired probability is also the same for both channels.

  • Using the given equation, we have

$${\rm Pr}(a \le 0.316) = {\rm Pr}(20 \cdot {\rm lg}\hspace{0.15cm} a \le -10\,\,{\rm dB}) = 1 - {\rm e}^{ -{0.316^2}/(2\sigma^2)}

= 1- 0.951 \hspace{0.15cm} \underline{ \approx 4.9 \%} 
\hspace{0.05cm}.$$


(3)  The correct solutions are 2, 3 and 6:

  • The smaller speed $v_{\rm B}$ can be recognized by the fact that the magnitude $|z(t)|$ changes more slowly with the blue curve.
  • When the vehicle is stationary, the PSD degenerates to ${\it \Phi_z}(f_{\rm D}) = 2\sigma^2\cdot \delta(f_{\rm D})$, and we have $|z(t)| = A = \rm const.$, where the constant $A$ is drawn from the Rayleigh distribution.
  • At extremely high speed, the Jakes spectrum becomes flat and has an increasingly smaller magnitude over an increasingly wide range. It then approaches the PSD of white noise. However, $v$ would have to be in the order of the speed of light.


(4)  Statements 2 and 3 are correct:

  • The Rayleigh parameter $\sigma = 1$ also determines the „power” ${\rm E}[|z(t)|^2] = 2\sigma^2 = 2$ of the random process.
  • This applies to both R and B:

$$\varphi_z ({\rm \delta}t = 0) = 2 \hspace{0.05cm}, \hspace{0.2cm} \int_{-\infty}^{+\infty}{\it \Phi}_z(f_{\rm D}) \hspace{0.15cm}{\rm d}f_{\rm D} = 2 \hspace{0.05cm}.$$