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Exercise 1.4: Rayleigh PDF and Jakes PDS

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PDF and  |z(t)|  for Rayleigh Fading with Doppler effect

We consider two different mobile radio channels with  Rayleigh fading. In both cases the PDF of the magnitude  a(t)=|z(t)|0  is

fa(a)=aσ2ea2/(2σ2).

The probability that this amount is not greater than a given value  A  is

Pr(|z(t)|A)=1eA2/(2σ2).

The two channels, which are designated according to the colors „Red” and „Blue” in the graphs with  R  and  B  respectively, differ in the speed  v  and thus in the form of the power spectral density (PSD)   Φz(fD).

  • For a Doppler frequency  fD  with  |fD|<fD,max  the Jakes spectrum is given by
πz(fD)=1πfD,max1(fD/fD,max)2.
  • For Doppler frequencies outside this interval from  fD,max  to  +fD,max,   we have πz(fD)=0.


The corresponding descriptor in the time domain is the autocorrelation function (ACF):

φz(δt)=2σ2J0(2πfD,maxδt).
  • Here,  J0(.)  is the Bessel function of the first kind and zeroth order. We have   J0(0)=1.
  • The maximum Doppler frequency of the channel model  R : is known to be   fD,max=200 Hz.
  • It is also known that the speeds  vR  and  vB  differ by the factor  2 .
  • Whether  vR  is twice as large as  vB  or vice versa, you should decide based on the above graphs.




Notes:




Questionns

1

Determine the Rayleigh parameter  σ  for the channels  R  and  B.

σR = 

  
σB = 

  

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.


Solutions

(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}.