Aufgaben:Exercise 1.4: Rayleigh PDF and Jakes PDS: Difference between revisions
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{{quiz-Header|Buchseite= | {{quiz-Header|Buchseite=Mobile_Communications/Statistical_Bindings_within_the_Rayleigh_Process}} | ||
[[File:P_ID2119__Mob_A_1_4.png|right|frame| | [[File:P_ID2119__Mob_A_1_4.png|right|frame| PDF and $|z(t)|$ for Rayleigh fading with Doppler effect]] | ||
We consider two different mobile radio channels with [[ | We consider two different mobile radio channels with [[Mobile_Communications/Wahrscheinlichkeitsdichte_des_Rayleigh%E2%80%93Fadings#Beispielhafte_Signalverl.C3.A4ufe_bei_Rayleigh.E2.80.93Fading|Rayleigh fading]]. In both cases the PDF of the magnitude $a(t) = |z(t)| ≥ 0$ is | ||
$$f_a(a) = \frac{a}{\sigma^2} \cdot {\rm e}^{ -{a^2}/(2\sigma^2)} | :$$f_a(a) = \frac{a}{\sigma^2} \cdot {\rm e}^{ -{a^2}/(2\sigma^2)}\hspace{0.05cm}.$$ | ||
The probability that this | The probability that this magnitude is not greater than a given value $A$ is | ||
$${\rm Pr}(|z(t)| \le A) = 1 - {\rm e}^{ -{A^2}/(2\sigma^2)} | :$${\rm Pr}(|z(t)| \le A) = 1 - {\rm e}^{ -{A^2}/(2\sigma^2)}\hspace{0.05cm}.$$ | ||
The two channels, which are designated according to the colors | 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 $\rm (PSD)$ ${\it \Phi}_z(f_{\rm D})$. | ||
*In both cases, however, the | *In both cases, however, the PDS is a [[Mobile_Communications/Statistical_bindings_within_the_Rayleigh_process|Jakes spectrum]]. | ||
*For a Doppler frequency $f_{\rm D}$ with $|f_{\rm D}| <f_{\rm D,\hspace{0. | *For a Doppler frequency $f_{\rm D}$ with $|f_{\rm D}| <f_{\rm D,\hspace{0.1cm}max}$ the Jakes spectrum is given by | ||
$${\it \ | :$${\it \Phi}_z(f_{\rm D}) = \frac{1}{\pi \hspace{-0.05cm}\cdot \hspace{-0.05cm}f_{\rm D, \hspace{0.1cm} max} \hspace{-0.05cm}\cdot \hspace{-0.05cm}\sqrt{ 1 \hspace{-0.05cm}- \hspace{-0.05cm}(f_{\rm D}/f_{\rm D, \hspace{0.1cm} max})^2} }\hspace{0.05cm}.$$ | ||
*Doppler frequencies outside this interval from $-f_{\rm D,\hspace{0. | *For Doppler frequencies outside this interval from $-f_{\rm D,\hspace{0.1cm}max}$ to $+f_{\rm D,\hspace{0.1cm}max}$, we have ${\it \Phi}_z(f_{\rm D})=0$. | ||
The corresponding descriptor in the time domain is the | The corresponding descriptor in the time domain is the auto-correlation function $\rm (ACF)$: | ||
$$\varphi_z ({\rm \delta}t) = 2 \sigma^2 \cdot {\rm J_0}(2\pi \cdot f_{\rm D, \hspace{0. | :$$\varphi_z ({\rm \delta}t) = 2 \sigma^2 \cdot {\rm J_0}(2\pi \cdot f_{\rm D, \hspace{0.1cm} max} \cdot {\rm \delta}t)\hspace{0.05cm}.$$ | ||
*Here | *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 | *The maximum Doppler frequency of the channel model $\rm R$ is known to be $f_{\rm D,\hspace{0.1cm}max} = 200 \ \rm Hz$. | ||
* It is also known that the speeds $v_{\rm R}$ and $v_{\rm B}$ differ by the factor $2$ . | * 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. | ||
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''Notes:'' | ''Notes:'' | ||
* | * This task belongs to the topic of [[Mobile_Communications/Statistical_Bindings_within_the_Rayleigh_Process#ACF_and_PDS_with_Rayleigh.E2.80.93Fading|Statistical bindings within the Rayleigh process]]. | ||
* To check your results you can use the interactive applet [[Applets: | * To check your results you can use the interactive applet [[Applets:PDF,_CDF_and_Moments_of_Special_Distributions|PDF, CDF and Moments of Special Distributions]]. | ||
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=== | ===Questionns=== | ||
<quiz display=simple> | <quiz display=simple> | ||
{Determine the Rayleigh | {Determine the Rayleigh parameter $\sigma$ for the channels $\rm R$ and $\rm B$. | ||
|type="{}"} | |type="{}"} | ||
$\sigma_{\rm R} \ = \ $ { 1 3% } $\ \ \rm $ | $\sigma_{\rm R} \ = \ $ { 1 3% } $\ \ \rm $ | ||
$\sigma_{\rm B} \ = \ $ { 1 3% } $\ \ \rm $ | $\sigma_{\rm B} \ = \ $ { 1 3% } $\ \ \rm $ | ||
{In each case, | {In each case, give the probability that $20 \cdot {\rm lg} \ a ≤ -10 \ \ \ \rm dB$ ⇒ $a ≤ 0.316$. | ||
|type="{}"} | |type="{}"} | ||
Channel ${\rm R}\text{:} | Channel ${\rm R}\text{:} \hspace{0.4cm} {\rm Pr}(a ≤ 0.316) \ = \ $ { 4.9 3% } $\ \rm \%$ | ||
Channel ${\rm B}\text{:} | Channel ${\rm B}\text{:} \hspace{0.4cm} {\rm Pr}(a ≤ 0.316) \ = \ $ { 4.9 3% } $\ \rm \%$ | ||
{Which statements are correct regarding the driving speeds $v$ ? | {Which statements are correct regarding the driving speeds $v$ ? | ||
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- $v_{\rm B}$ is twice as big as $v_{\rm R}$. | - $v_{\rm B}$ is twice as big as $v_{\rm R}$. | ||
+ $v_{\rm B}$ is half as big as $v_{\rm R}$. | + $v_{\rm B}$ is half as big as $v_{\rm R}$. | ||
+ With $v = 0$ | + With $v = 0$, $|z(t)|$ would be constant. | ||
- With $v = 0$ | - With $v = 0$, $|z(t)|$ would have a white spectrum. | ||
- With $v → ∞$ | - With $v → ∞$, $|z(t)|$ would be constant. | ||
+ With $v → ∞$ | + With $v → ∞$, $|z(t)|$ would be white. | ||
{Which of the following statements are correct? | {Which of the following statements are correct? | ||
|type="[]"} | |type="[]"} | ||
- The | - The PDS value ${\it \Phi_z}(f_{\rm D} = 0)$ is the same for both channels. | ||
+ The | + 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 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. | - The area below $\varphi_z(\Delta t)$ is the same for both channels. | ||
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=== | ===Solution=== | ||
{{ML-Kopf}} | {{ML-Kopf}} | ||
'''(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 | *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}.$$ | ||
*By | *By setting the derivative to $0$, you can show that the maximum of the PDF occurs at $a = \sigma$. Since the Rayleigh PDF applies to both channels, it follows that | ||
$$\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}.$$ | ||
'''(2)''' | '''(2)''' As they fading coefficients have the same PDF, the desired probability is also the same for both channels. | ||
* | *Using the given equation, we have | ||
$${\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)} | :$${\rm Pr}(a \le 0.316) = {\rm Pr}(20 \cdot {\rm lg}\hspace{0.15cm} a \le -10\,\,{\rm dB}) = 1 - {\rm e}^{ -{0.316^2}/(2\sigma^2)}= 1- 0.951 \hspace{0.15cm} \underline{ \approx 4.9 \%}\hspace{0.05cm}.$$ | ||
'''(3)''' <u>The correct | '''(3)''' <u>The correct statements are 2, 3 and 6</u>: | ||
* The smaller speed $v_{\rm B}$ can be recognized by the fact that the | * 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 PDS 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 | * At extremely high speed, the Jakes spectrum becomes flat and has an increasingly small magnitude over an increasingly wide range. It then approaches the PDS of white noise. However, $v$ would have to be in the order of the speed of light. | ||
'''(4)''' | '''(4)''' <u>Statements 2 and 3</u> are correct: | ||
*The Rayleigh& | *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 | *This applies to both $\rm R$ and $\rm B$: | ||
$$\varphi_z ({\rm \delta}t = 0) = 2 \hspace{0.05cm}, \hspace{0.2cm} \int_{-\infty}^{+\infty}{\it \Phi}_z(f_{\rm D}) \hspace{0.15cm}{\rm d}f_{\rm D} = 2 \hspace{0.05cm}.$$ | :$$\varphi_z ({\rm \delta}t = 0) = 2 \hspace{0.05cm}, \hspace{0.2cm} \int_{-\infty}^{+\infty}{\it \Phi}_z(f_{\rm D}) \hspace{0.15cm}{\rm d}f_{\rm D} = 2 \hspace{0.05cm}.$$ | ||
{{ML-Fuß}} | {{ML-Fuß}} | ||
[[Category: | [[Category:Mobile Communications: Exercises|^1.3 Rayleigh Fading with Memory^]] | ||
Latest revision as of 15:47, 16 March 2026

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 magnitude 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 $\rm (PSD)$ ${\it \Phi}_z(f_{\rm D})$.
- In both cases, however, the PDS is a Jakes spectrum.
- For a Doppler frequency $f_{\rm D}$ with $|f_{\rm D}| <f_{\rm D,\hspace{0.1cm}max}$ the Jakes spectrum is given by
- $${\it \Phi}_z(f_{\rm D}) = \frac{1}{\pi \hspace{-0.05cm}\cdot \hspace{-0.05cm}f_{\rm D, \hspace{0.1cm} max} \hspace{-0.05cm}\cdot \hspace{-0.05cm}\sqrt{ 1 \hspace{-0.05cm}- \hspace{-0.05cm}(f_{\rm D}/f_{\rm D, \hspace{0.1cm} max})^2} }\hspace{0.05cm}.$$
- For Doppler frequencies outside this interval from $-f_{\rm D,\hspace{0.1cm}max}$ to $+f_{\rm D,\hspace{0.1cm}max}$, we have ${\it \Phi}_z(f_{\rm D})=0$.
The corresponding descriptor in the time domain is the auto-correlation function $\rm (ACF)$:
- $$\varphi_z ({\rm \delta}t) = 2 \sigma^2 \cdot {\rm J_0}(2\pi \cdot f_{\rm D, \hspace{0.1cm} max} \cdot {\rm \delta}t)\hspace{0.05cm}.$$
- 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 $f_{\rm D,\hspace{0.1cm}max} = 200 \ \rm Hz$.
- 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:
- This task belongs to the topic of Statistical bindings within the Rayleigh process.
- To check your results you can use the interactive applet PDF, CDF and Moments of Special Distributions.
Questionns
Solution
- 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 statements 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 PDS 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 small magnitude over an increasingly wide range. It then approaches the PDS 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 $\rm R$ and $\rm B$:
- $$\varphi_z ({\rm \delta}t = 0) = 2 \hspace{0.05cm}, \hspace{0.2cm} \int_{-\infty}^{+\infty}{\it \Phi}_z(f_{\rm D}) \hspace{0.15cm}{\rm d}f_{\rm D} = 2 \hspace{0.05cm}.$$