Aufgaben:Exercise 2.7: Coherence Bandwidth: Difference between revisions

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* The &nbsp;<b>multipath spread</b> or <b>delay spread</b>&nbsp; $\sigma_{\rm V}$&nbsp; gives the standard deviation of the random variable&nbsp; $\tau$&nbsp;.&nbsp; In the theory part we also use the term&nbsp; $T_{\rm V}$ for this.
* The &nbsp;<b>multipath spread</b> or <b>delay spread</b>&nbsp; $\sigma_{\rm V}$&nbsp; gives the standard deviation of the random variable&nbsp; $\tau$&nbsp;.&nbsp; In the theory part we also use the term&nbsp; $T_{\rm V}$ for this.
* The displayed frequency correlation function&nbsp; $\varphi_{\rm F}(\Delta f)$&nbsp; can be calculated as the Fourier transform of the delay power-spectral density&nbsp; ${\it \Phi}_{\rm V}(\tau)$&nbsp;:
* The displayed frequency correlation function&nbsp; $\varphi_{\rm F}(\Delta f)$&nbsp; can be calculated as the Fourier transform of the delay power-spectral density&nbsp; ${\it \Phi}_{\rm V}(\tau)$&nbsp;:
:$$\varphi_{\rm F}(\Delta f)
:$$\varphi_{\rm F}(\Delta f)\hspace{0.2cm}  {\bullet\!\!-\!\!\!-\!\!\!-\!\!\circ} \hspace{0.2cm} {\it \Phi}_{\rm V}(\tau)\hspace{0.05cm}.$$
\hspace{0.2cm}  {\bullet\!\!-\!\!\!-\!\!\!-\!\!\circ} \hspace{0.2cm} {\it \Phi}_{\rm V}(\tau)\hspace{0.05cm}.$$
* The <b>coherence bandwidth</b>&nbsp; $B_{\rm K}$&nbsp; is the value of $\Delta f$ at which the frequency correlation function&nbsp; $\varphi_{\rm F}(\Delta f)$&nbsp; has dropped to half in absolute value.
* The <b>coherence bandwidth</b>&nbsp; $B_{\rm K}$&nbsp; is the value of $\Delta f$ at which the frequency correlation function&nbsp; $\varphi_{\rm F}(\Delta f)$&nbsp; has dropped to half in absolute value.


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* This exercise requires knowledge of&nbsp; [[Theory_of_Stochastic_Signals/Expected_Values_and_Moments|Expected values and moments]]&nbsp; from the book "Theory of Stochastic Signals".
* This exercise requires knowledge of&nbsp; [[Theory_of_Stochastic_Signals/Expected_Values_and_Moments|Expected values and moments]]&nbsp; from the book "Theory of Stochastic Signals".
* In addition, the following Fourier transform is given:
* In addition, the following Fourier transform is given:
:$$x(t) = \left\{ \begin{array}{c} {\rm e}^{- \lambda \hspace{0.05cm}\cdot \hspace{0.05cm} t}\\
:$$x(t) = \left\{ \begin{array}{c} {\rm e}^{- \lambda \hspace{0.05cm}\cdot \hspace{0.05cm} t}\\0  \end{array} \right.\quad\begin{array}{*{1}c} \hspace{-0.35cm} {\rm for} \hspace{0.15cm} t \ge 0\\ \hspace{-0.35cm} {\rm for} \hspace{0.15cm} t < 0 \\ \end{array}\hspace{0.4cm}  {\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet} \hspace{0.4cm} X(f) = \frac{1}{\lambda + {\rm j} \cdot 2\pi f}\hspace{0.05cm}.$$
0  \end{array} \right.\quad
\begin{array}{*{1}c} \hspace{-0.35cm} {\rm for} \hspace{0.15cm} t \ge 0
\\ \hspace{-0.35cm} {\rm for} \hspace{0.15cm} t < 0 \\ \end{array}  
\hspace{0.4cm}  {\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet} \hspace{0.4cm} X(f) = \frac{1}{\lambda + {\rm j} \cdot 2\pi f}\hspace{0.05cm}.$$
   
   


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'''(1)'''&nbsp; Let&nbsp; ${\it \Phi}_0 = {\it \Phi}_{\rm V}(\tau = 0)$.&nbsp; The integral of the delay power-spectral density gives
'''(1)'''&nbsp; Let&nbsp; ${\it \Phi}_0 = {\it \Phi}_{\rm V}(\tau = 0)$.&nbsp; The integral of the delay power-spectral density gives
:$$\int_{0}^{+\infty} {\it \Phi}_{\rm V}(\tau) \hspace{0.15cm}{\rm d} \tau =
:$$\int_{0}^{+\infty} {\it \Phi}_{\rm V}(\tau) \hspace{0.15cm}{\rm d} \tau ={\it \Phi}_{\rm 0} \cdot \int_{0}^{+\infty} {\rm e}^{-\tau / \tau_0} \hspace{0.15cm}{\rm d} \tau ={\it \Phi}_{\rm 0} \cdot \tau_0\hspace{0.05cm}. $$
{\it \Phi}_{\rm 0} \cdot \int_{0}^{+\infty} {\rm e}^{-\tau / \tau_0} \hspace{0.15cm}{\rm d} \tau =  
{\it \Phi}_{\rm 0} \cdot \tau_0
\hspace{0.05cm}. $$


*Then the probability density function is
*Then the probability density function is
:$$f_{\rm V}(\tau)  = \frac{{\it \Phi}_{\rm V}(\tau) }{{\it \Phi}_{\rm 0} \cdot \tau_0}= \frac{1}{\tau_0} \cdot  {\rm e}^{-\tau / \tau_0}  
:$$f_{\rm V}(\tau)  = \frac{{\it \Phi}_{\rm V}(\tau) }{{\it \Phi}_{\rm 0} \cdot \tau_0}= \frac{1}{\tau_0} \cdot  {\rm e}^{-\tau / \tau_0}\hspace{0.05cm}.$$
\hspace{0.05cm}.$$


*<u>Solution 2</u> is correct.
*<u>Solution 2</u> is correct.
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'''(2)'''&nbsp; The&nbsp; $k$-th moment of an&nbsp; [[Theory_of_Stochastic_Signals/Exponentially_Distributed_Random_Variables#One-sided_exponential_distribution|one-sided exponential random variable]]&nbsp; is&nbsp; $m_k = k! \cdot \tau_0^k$.  
'''(2)'''&nbsp; The&nbsp; $k$-th moment of an&nbsp; [[Theory_of_Stochastic_Signals/Exponentially_Distributed_Random_Variables#One-sided_exponential_distribution|one-sided exponential random variable]]&nbsp; is&nbsp; $m_k = k! \cdot \tau_0^k$.  
*With&nbsp; $k = 1$, this results in the linear mean value&nbsp; $m_1 = m_{\rm V}$:
*With&nbsp; $k = 1$, this results in the linear mean value&nbsp; $m_1 = m_{\rm V}$:
:$$m_{\rm V} = \tau_0 \hspace{0.1cm} \underline {= 1\,{\rm &micro; s}}
:$$m_{\rm V} = \tau_0 \hspace{0.1cm} \underline {= 1\,{\rm &micro; s}}\hspace{0.05cm}. $$
  \hspace{0.05cm}. $$




'''(3)'''&nbsp; According to the&nbsp; [[Theory_of_Stochastic_Signals/Erwartungswerte_und_Momente#Some common central moments| Steiner's Theorem]], the  variance of any random variable is&nbsp; $\sigma^2 = m_2 \, -m_1^2$.  
'''(3)'''&nbsp; According to the&nbsp; [[Theory_of_Stochastic_Signals/Expected_Values_and_Moments#Some_common_central_moments| Steiner's Theorem]], the  variance of any random variable is&nbsp; $\sigma^2 = m_2 \, -m_1^2$.  
*This yields&nbsp; $m_2 = 2 \cdot \tau_0^2$, and therefore
*This yields&nbsp; $m_2 = 2 \cdot \tau_0^2$, and therefore
:$$\sigma_{\rm V}^2 = m_2 - m_1^2 = 2 \cdot \tau_0^2 - (\tau_0)^2 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
:$$\sigma_{\rm V}^2 = m_2 - m_1^2 = 2 \cdot \tau_0^2 - (\tau_0)^2 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}\sigma_{\rm V} = \tau_0 \hspace{0.1cm} \underline {= 1\,{\rm &micro; s}}\hspace{0.05cm}.  $$
  \sigma_{\rm V} = \tau_0 \hspace{0.1cm} \underline {= 1\,{\rm &micro; s}}
  \hspace{0.05cm}.  $$




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'''(4)'''&nbsp; ${\it \Phi}_{\rm V}(\tau)$&nbsp; is identical to&nbsp; $x(t)$&nbsp; in the given Fourier transform pair if&nbsp; $t$&nbsp; is replaced by&nbsp; $\tau$&nbsp; and&nbsp; $\lambda$&nbsp; by&nbsp; $1/\tau_0$.  
'''(4)'''&nbsp; ${\it \Phi}_{\rm V}(\tau)$&nbsp; is identical to&nbsp; $x(t)$&nbsp; in the given Fourier transform pair if&nbsp; $t$&nbsp; is replaced by&nbsp; $\tau$&nbsp; and&nbsp; $\lambda$&nbsp; by&nbsp; $1/\tau_0$.  
*Thus,&nbsp; $\varphi_{\rm F}(\Delta f)$&nbsp; is equal to&nbsp; $X(f)$&nbsp; with the substitution&nbsp; $f &#8594; \Delta f$:
*Thus,&nbsp; $\varphi_{\rm F}(\Delta f)$&nbsp; is equal to&nbsp; $X(f)$&nbsp; with the substitution&nbsp; $f &#8594; \Delta f$:
:$$\varphi_{\rm F}(\Delta f) = \frac{1}{1/\tau_0 + {\rm j} \cdot 2\pi \Delta f}
:$$\varphi_{\rm F}(\Delta f) = \frac{1}{1/\tau_0 + {\rm j} \cdot 2\pi \Delta f}= \frac{\tau_0}{1 + {\rm j} \cdot 2\pi \cdot \tau_0 \cdot \Delta f}\hspace{0.05cm}.$$
= \frac{\tau_0}{1 + {\rm j} \cdot 2\pi \cdot \tau_0 \cdot \Delta f}\hspace{0.05cm}.$$


*The <u>first expression</u> is correct.
*The <u>first expression</u> is correct.
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'''(5)'''&nbsp; The coherence bandwidth is implicit in the following equation:
'''(5)'''&nbsp; The coherence bandwidth is implicit in the following equation:
:$$|\varphi_{\rm F}(\Delta f = B_{\rm K})| \stackrel {!}{=} \frac{1}{2} \cdot |\varphi_{\rm F}(\Delta f = 0)| = \frac{\tau_0}{2}\hspace{0.3cm}
:$$|\varphi_{\rm F}(\Delta f = B_{\rm K})| \stackrel {!}{=} \frac{1}{2} \cdot |\varphi_{\rm F}(\Delta f = 0)| = \frac{\tau_0}{2}\hspace{0.3cm}\Rightarrow \hspace{0.3cm}|\varphi_{\rm F}(\Delta f = B_{\rm K})|^2= \frac{\tau_0^2}{1 + (2\pi \cdot \tau_0 \cdot B_{\rm K})^2} \stackrel  {!}{=} \frac{\tau_0^2}{4}$$
\Rightarrow \hspace{0.3cm}|\varphi_{\rm F}(\Delta f = B_{\rm K})|^2  
:$$\Rightarrow \hspace{0.3cm}(2\pi \cdot \tau_0 \cdot B_{\rm K})^2 = 3 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}B_{\rm K}= \frac{\sqrt{3}}{2\pi \cdot \tau_0} \approx \frac{0.276}{ \tau_0}\hspace{0.05cm}. $$
= \frac{\tau_0^2}{1 + (2\pi \cdot \tau_0 \cdot B_{\rm K})^2} \stackrel  {!}{=} \frac{\tau_0^2}{4}$$
:$$\Rightarrow \hspace{0.3cm}(2\pi \cdot \tau_0 \cdot B_{\rm K})^2 = 3 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
B_{\rm K}= \frac{\sqrt{3}}{2\pi \cdot \tau_0} \approx \frac{0.276}{ \tau_0}\hspace{0.05cm}. $$


*With&nbsp; $\tau_0 = 1 \ \ \rm &micro; s$, the coherence bandwidth is&nbsp; $B_{\rm K} \ \underline {= 276 \ \ \rm kHz}$.
*With&nbsp; $\tau_0 = 1 \ \ \rm &micro; s$, the coherence bandwidth is&nbsp; $B_{\rm K} \ \underline {= 276 \ \ \rm kHz}$.
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[[Category:Mobile Communications: Exercises|^2.3 The GWSSUS Channel Model^]]
[[Category:Mobile Communications: Exercises|^2.3 The GWSSUS Channel Model^]]
[[de:Exercises:Exercise_2.7:_Coherence_Bandwidth]]

Latest revision as of 15:30, 16 March 2026

Delay power-spectral density and
frequency correlation function

For the delay power-spectral density, we assume an exponential behavior.  With  ${\it \Phi}_0 = {\it \Phi}_{\rm V}(\tau = 0)$  we have

$${{\it \phi}_{\rm V}(\tau)}/{{\it \phi}_{\rm 0}} = {\rm e}^{ -\tau / \tau_0 } \hspace{0.05cm}.$$

The constant  $\tau_0$  can be determined from the tangent in the point  $\tau = 0$  according to the upper graph.  Note that  ${\it \Phi}_{\rm V}(\tau)$  has unit  $[1/\rm s]$ .  Furthermore,

  • The probability density function  $\rm (PDF)$  $f_{\rm V}(\tau)$  has the same form as  ${\it \Phi}_{\rm V}(\tau)$, but is normalized to area  $1$ .
  • The  average excess delay or mean excess delay  $m_{\rm V}$  is equal to the linear expectation  $E\big [\tau \big]$  and can be determined from the PDF $f_{\rm V}(\tau)$ .
  • The  multipath spread or delay spread  $\sigma_{\rm V}$  gives the standard deviation of the random variable  $\tau$ .  In the theory part we also use the term  $T_{\rm V}$ for this.
  • The displayed frequency correlation function  $\varphi_{\rm F}(\Delta f)$  can be calculated as the Fourier transform of the delay power-spectral density  ${\it \Phi}_{\rm V}(\tau)$ :
$$\varphi_{\rm F}(\Delta f)\hspace{0.2cm} {\bullet\!\!-\!\!\!-\!\!\!-\!\!\circ} \hspace{0.2cm} {\it \Phi}_{\rm V}(\tau)\hspace{0.05cm}.$$
  • The coherence bandwidth  $B_{\rm K}$  is the value of $\Delta f$ at which the frequency correlation function  $\varphi_{\rm F}(\Delta f)$  has dropped to half in absolute value.




Notes:

$$x(t) = \left\{ \begin{array}{c} {\rm e}^{- \lambda \hspace{0.05cm}\cdot \hspace{0.05cm} t}\\0 \end{array} \right.\quad\begin{array}{*{1}c} \hspace{-0.35cm} {\rm for} \hspace{0.15cm} t \ge 0\\ \hspace{-0.35cm} {\rm for} \hspace{0.15cm} t < 0 \\ \end{array}\hspace{0.4cm} {\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet} \hspace{0.4cm} X(f) = \frac{1}{\lambda + {\rm j} \cdot 2\pi f}\hspace{0.05cm}.$$



Questionnaire

1 What is the probability density function  $f_{\rm V}(\tau)$  of the delay time?

$f_{\rm V}(\tau) = {\rm e}^{-\tau/\tau_0}$.
$f_{\rm V}(\tau) = 1/\tau_0 \cdot {\rm e}^{-\tau/\tau_0}$,
$f_{\rm V}(\tau) = {\it \Phi}_0 \cdot {\rm e}^{-\tau/\tau_0}$.

2 Determine the average delay time for  $\tau_0 = 1 \ \ \rm µ s$.

$m_{\rm V} \ = \ $ $\ \rm µ s$

3 Which value results for the multipath spread with  $\tau_0 = 1 \ \ \rm µ s$?

$\sigma_{\rm V} \ = \ $ $\ \rm µ s$

4 What is the frequency–correlation function  $\varphi_{\rm F}(\Delta f)$?

$\varphi_{\rm F}(\Delta f) = \big[1/\tau_0 + {\rm j} \ 2 \pi \cdot \delta f \big]^{-1}$,
$\varphi_{\rm F}(\Delta f) = {\rm e}^ {-(\tau_0 \hspace{0.05cm}\cdot \hspace{0.05cm}\Delta f)^2}$.

5 Determine the coherence bandwidth  $B_{\rm K}$.

$B_{\rm K} \ = \ $ $\ \ \rm kHz$


Solution

(1)  Let  ${\it \Phi}_0 = {\it \Phi}_{\rm V}(\tau = 0)$.  The integral of the delay power-spectral density gives

$$\int_{0}^{+\infty} {\it \Phi}_{\rm V}(\tau) \hspace{0.15cm}{\rm d} \tau ={\it \Phi}_{\rm 0} \cdot \int_{0}^{+\infty} {\rm e}^{-\tau / \tau_0} \hspace{0.15cm}{\rm d} \tau ={\it \Phi}_{\rm 0} \cdot \tau_0\hspace{0.05cm}. $$
  • Then the probability density function is
$$f_{\rm V}(\tau) = \frac{{\it \Phi}_{\rm V}(\tau) }{{\it \Phi}_{\rm 0} \cdot \tau_0}= \frac{1}{\tau_0} \cdot {\rm e}^{-\tau / \tau_0}\hspace{0.05cm}.$$
  • Solution 2 is correct.


(2)  The  $k$-th moment of an  one-sided exponential random variable  is  $m_k = k! \cdot \tau_0^k$.

  • With  $k = 1$, this results in the linear mean value  $m_1 = m_{\rm V}$:
$$m_{\rm V} = \tau_0 \hspace{0.1cm} \underline {= 1\,{\rm µ s}}\hspace{0.05cm}. $$


(3)  According to the  Steiner's Theorem, the variance of any random variable is  $\sigma^2 = m_2 \, -m_1^2$.

  • This yields  $m_2 = 2 \cdot \tau_0^2$, and therefore
$$\sigma_{\rm V}^2 = m_2 - m_1^2 = 2 \cdot \tau_0^2 - (\tau_0)^2 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}\sigma_{\rm V} = \tau_0 \hspace{0.1cm} \underline {= 1\,{\rm µ s}}\hspace{0.05cm}. $$


(4)  ${\it \Phi}_{\rm V}(\tau)$  is identical to  $x(t)$  in the given Fourier transform pair if  $t$  is replaced by  $\tau$  and  $\lambda$  by  $1/\tau_0$.

  • Thus,  $\varphi_{\rm F}(\Delta f)$  is equal to  $X(f)$  with the substitution  $f → \Delta f$:
$$\varphi_{\rm F}(\Delta f) = \frac{1}{1/\tau_0 + {\rm j} \cdot 2\pi \Delta f}= \frac{\tau_0}{1 + {\rm j} \cdot 2\pi \cdot \tau_0 \cdot \Delta f}\hspace{0.05cm}.$$
  • The first expression is correct.


(5)  The coherence bandwidth is implicit in the following equation:

$$|\varphi_{\rm F}(\Delta f = B_{\rm K})| \stackrel {!}{=} \frac{1}{2} \cdot |\varphi_{\rm F}(\Delta f = 0)| = \frac{\tau_0}{2}\hspace{0.3cm}\Rightarrow \hspace{0.3cm}|\varphi_{\rm F}(\Delta f = B_{\rm K})|^2= \frac{\tau_0^2}{1 + (2\pi \cdot \tau_0 \cdot B_{\rm K})^2} \stackrel {!}{=} \frac{\tau_0^2}{4}$$
$$\Rightarrow \hspace{0.3cm}(2\pi \cdot \tau_0 \cdot B_{\rm K})^2 = 3 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}B_{\rm K}= \frac{\sqrt{3}}{2\pi \cdot \tau_0} \approx \frac{0.276}{ \tau_0}\hspace{0.05cm}. $$
  • With  $\tau_0 = 1 \ \ \rm µ s$, the coherence bandwidth is  $B_{\rm K} \ \underline {= 276 \ \ \rm kHz}$.