Difference between revisions of "Aufgaben:Exercise 1.4: Rayleigh PDF and Jakes PDS"
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[[File:P_ID2119__Mob_A_1_4.png|right|frame| WDF und $|z(t)|$ bei Rayleigh-Fading mit Dopplereinfluss]] | [[File:P_ID2119__Mob_A_1_4.png|right|frame| WDF und $|z(t)|$ bei Rayleigh-Fading mit Dopplereinfluss]] | ||
− | + | We consider two different mobile radio channels with [[Mobile_Communication/Probability_Density_of_Rayleigh%E2%80%93Fadings#Example_Signal_loss.C3.A4ufe_bei_Rayleigh.E2.80.93Fading|Rayleigh–Fading]]. In both cases the WDF of the amount $a(t) = |z(t)| ≥ 0$ can be represented in the following way: | |
− | + | $$f_a(a) = \frac{a}{\sigma^2} \cdot {\rm e}^{ -{a^2}/(2\sigma^2)} | |
\hspace{0.05cm}.$$ | \hspace{0.05cm}.$$ | ||
− | + | The probability that this amount is not greater than a given value $A$ can be calculated as follows | |
− | + | $${\rm Pr}(|z(t)| \le A) = 1 - {\rm e}^{ -{A^2}/(2\sigma^2)} | |
\hspace{0.05cm}.$$ | \hspace{0.05cm}.$$ | ||
− | + | The two channels, which are designated according to the colors „Red” and „Blue” in the graphics with $\rm R$ and $\rm B$ respectively, differ in the speed $v$ and thus in the form of the power density spectrum ${\it \Phi}_z(f_{\rm D})$. | |
− | *In | + | *In both cases, however, a so-called [[Mobile_Communication/Statistical_Bonds_within_Rayleigh%E2%80%93Process#AKF_and_LDS_at_Rayleigh.E2.80.93Fading|Jakes–Spectrum]] results. |
− | * | + | *For a Doppler frequency $f_{\rm D}$ with $|f_{\rm D}| <f_{\rm D,\hspace{0.05cm}max}$ the equation is |
− | + | $${\it \pi}_z(f_{\rm D}) = \frac{1}{\pi \hspace{-0.05cm}\cdot \hspace{-0.05cm}f_{\rm D, \hspace{0.05cm} max} \hspace{-0.05cm}\cdot \hspace{-0.05cm}\sqrt{ 1 \hspace{-0.05cm}- \hspace{-0.05cm}(f_{\rm D}/f_{\rm D, \hspace{0.05cm} max})^2} } | |
\hspace{0.05cm}.$$ | \hspace{0.05cm}.$$ | ||
− | * | + | *Doppler frequencies outside this interval from $-f_{\rm D,\hspace{0.05cm}max}$ to $+f_{\rm D,\hspace{0.05cm}max}$ are excluded. |
− | + | The corresponding descriptor in the time domain is the autocorrelation function (ACF): | |
− | + | $$\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 denoted ${\rm J_0}(.)$ the <i>first-order and zero-order Bessel function</i>. It applies ${\rm J_0}(0) = 1$. |
− | * | + | *The maximum Doppler frequency is known from the channel model $\rm R$ : $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$ . |
− | *Ob $v_{\rm R}$ | + | *Ob $v_{\rm R}$ is twice as large as $v_{\rm B}$ or vice versa, you should decide based on the above graphics. |
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− | '' | + | ''Notes:'' |
− | * | + | * The task belongs to the topic of [[Mobile_Communication/Statistical_Bonds_within_the_Rayleigh%E2%80%93Process|Statistical_Bondswithin_the_Rayleigh–Process]]. |
− | * | + | * To check your results you can use the interactive applet [[Applets:WDF_VTF|WDF, VTF and Moments]] . |
Line 45: | Line 45: | ||
− | === | + | ===Questionnaire=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {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, state the probability that $20 \cdot {\rm lg} \ a ≤ –10 \ \ \ \rm dB$ which is also $a ≤ 0.316$ at the same time. |
|type="{}"} | |type="{}"} | ||
− | + | Channel ${\rm R}\text{:} {\hspace{0.4cm} {\rm Pr}(a ≤ 0.316) \ = \ $ { 4.9 3% } $\ \rm \%$ | |
− | + | 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$ ? |
|type="[]"} | |type="[]"} | ||
− | - $v_{\rm B}$ | + | - $v_{\rm B}$ is twice as big as $v_{\rm R}$. |
− | + $v_{\rm B}$ | + | + $v_{\rm B}$ is half as big as $v_{\rm R}$. |
− | + | + | + With $v = 0$ would be $|z(t)|$ constant. |
− | - | + | - With $v = 0$ would be $|z(t)|$ spectrally seen white. |
− | - | + | - With $v → ∞$ would be $|z(t)|$ constant. |
− | + | + | + With $v → ∞$ would be $|z(t)|$ white. |
− | { | + | {Which of the following statements are correct? |
|type="[]"} | |type="[]"} | ||
− | - | + | - The LDS–value ${\it \Phi_z}(f_{\rm D} = 0)$ is the same for both channels. |
− | + | + | + The AKF–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. |
</quiz> | </quiz> | ||
− | === | + | ===Sample solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(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 |
:$$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{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 |
− | + | $$\sigma_{\rm R} = \sigma_{\rm B} \hspace{0.15cm} \underline{ = 1} \hspace{0.05cm}.$$ | |
− | '''(2)''' | + | '''(2)''' Because of the same WDF, the searched probability is also the same for both channels. |
− | * | + | *With the given equation you get for this |
− | + | $${\rm Pr}(a \le 0.316) = {\rm Pr}(20 \cdot {\rm lg}\hspace{0.15cm} a \le -10\,\,{\rm dB}) = 1 - {\rm e}^{ -{0.316^2}/(2\sigma^2)} | |
= 1- 0.951 \hspace{0.15cm} \underline{ \approx 4.9 \%} | = 1- 0.951 \hspace{0.15cm} \underline{ \approx 4.9 \%} | ||
\hspace{0.05cm}.$$ | \hspace{0.05cm}.$$ | ||
− | '''(3)''' <u> | + | '''(3)''' <u>The correct solutions are 2, 3 and 6</u>: |
− | * | + | * The smaller speed $v_{\rm B}$ can be recognized by the fact that the amount $|z(t)|$ changes more slowly with the blue curve. |
− | * | + | * With the vehicle stationary, the LDS degenerates to ${\it \Phi_z}(f_{\rm D}) = 2\sigma^2\cdot \delta(f_{\rm D})$, and it is $|z(t)| = A = \rm const.$, where the constant $A$ is diced according to the Rayleigh distribution. |
− | * | + | * At extremely high speed, the Jakes–spectrum becomes flat and lower over an increasingly wide range. It then approaches the LDS of white noise. However, $v$ would have to be in the order of the speed of light. |
− | '''(4)''' | + | '''(4)''' Correct are the <u>statements 2 and 3</u>: |
− | * | + | *The Rayleigh–parameter $\sigma = 1$ also determines the „power” ${\rm E}[|z(t)|^2] = 2\sigma^2 = 2$ of the random process. |
− | * | + | *This applies to both '''R''' and '''B''': |
− | + | $$\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}.$$ | |
{{ML-Fuß}} | {{ML-Fuß}} | ||
Revision as of 18:22, 25 March 2020
We consider two different mobile radio channels with Rayleigh–Fading. In both cases the WDF of the amount $a(t) = |z(t)| ≥ 0$ can be represented in the following way: $$f_a(a) = \frac{a}{\sigma^2} \cdot {\rm e}^{ -{a^2}/(2\sigma^2)} \hspace{0.05cm}.$$
The probability that this amount is not greater than a given value $A$ can be calculated as follows $${\rm Pr}(|z(t)| \le A) = 1 - {\rm e}^{ -{A^2}/(2\sigma^2)} \hspace{0.05cm}.$$
The two channels, which are designated according to the colors „Red” and „Blue” in the graphics with $\rm R$ and $\rm B$ respectively, differ in the speed $v$ and thus in the form of the power density spectrum ${\it \Phi}_z(f_{\rm D})$.
- In both cases, however, a so-called Jakes–Spectrum results.
- For a Doppler frequency $f_{\rm D}$ with $|f_{\rm D}| <f_{\rm D,\hspace{0.05cm}max}$ the equation is
$${\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}.$$
- Doppler frequencies outside this interval from $-f_{\rm D,\hspace{0.05cm}max}$ to $+f_{\rm D,\hspace{0.05cm}max}$ are excluded.
The corresponding descriptor in the time domain is the autocorrelation function (ACF):
$$\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}.$$
- Here denoted ${\rm J_0}(.)$ the first-order and zero-order Bessel function. It applies ${\rm J_0}(0) = 1$.
- The maximum Doppler frequency is known from the channel model $\rm R$ : $f_{\rm D,\hspace{0.05cm}max} = 200 \ \rm Hz$.
- It is also known that the speeds $v_{\rm R}$ and $v_{\rm B}$ differ by the factor $2$ .
- Ob $v_{\rm R}$ is twice as large as $v_{\rm B}$ or vice versa, you should decide based on the above graphics.
Notes:
- The task belongs to the topic of Statistical_Bondswithin_the_Rayleigh–Process.
- To check your results you can use the interactive applet WDF, VTF and Moments .
Questionnaire
Sample solution
- The Rayleigh–WDF and its derivation are general
- $$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}.$$
- By zeroing the derivative, you can show that the WDF–maximum occurs at $a = \sigma$. Since the Rayleigh–WDF applies to both channels, it follows that
$$\sigma_{\rm R} = \sigma_{\rm B} \hspace{0.15cm} \underline{ = 1} \hspace{0.05cm}.$$
(2) Because of the same WDF, the searched probability is also the same for both channels.
- With the given equation you get for this
$${\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}.$$
(3) The correct solutions are 2, 3 and 6:
- The smaller speed $v_{\rm B}$ can be recognized by the fact that the amount $|z(t)|$ changes more slowly with the blue curve.
- With the vehicle stationary, the LDS degenerates to ${\it \Phi_z}(f_{\rm D}) = 2\sigma^2\cdot \delta(f_{\rm D})$, and it is $|z(t)| = A = \rm const.$, where the constant $A$ is diced according to the Rayleigh distribution.
- At extremely high speed, the Jakes–spectrum becomes flat and lower over an increasingly wide range. It then approaches the LDS of white noise. However, $v$ would have to be in the order of the speed of light.
(4) Correct are the statements 2 and 3:
- The Rayleigh–parameter $\sigma = 1$ also determines the „power” ${\rm E}[|z(t)|^2] = 2\sigma^2 = 2$ of the random process.
- This applies to both R and B:
$$\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}.$$