Difference between revisions of "Mobile Communications/Multi-Path Reception in Mobile Communications"

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== Simple time invariant model of the two-way channel==
+
== Simple time–invariant model of the two-way channel==
 
<br>
 
<br>
[[File:EN_Mob_T_2_2_S1b.png|right|frame|Replacement model for the two-way channel]]  
+
[[File:EN_Mob_T_2_2_S1b.png|right|frame|Simple model for the two-way channel]]  
 
For the frequency selectivity
 
For the frequency selectivity
 
*the path loss&nbsp; $($marked by&nbsp; $k_1)$&nbsp; and  
 
*the path loss&nbsp; $($marked by&nbsp; $k_1)$&nbsp; and  
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We will now describe the two-way channel with the new parameters&nbsp;  
 
We will now describe the two-way channel with the new parameters&nbsp;  
:$$k_0 = |k_2 /k_1 |,$$
+
:$$k_0 = |k_2 /k_1 |,\hspace{0.5cm} \tau_0 = \tau_2 - \tau_1.$$
:$$\tau_0 = \tau_2 - \tau_1.$$
 
  
 
This results in:
 
This results in:
 
::<math>r(t) = r_1(t) + k_0 \cdot r_1( t - \tau_0) \hspace{0.5cm}{\rm with} \hspace{0.5cm} r_1(t) = k_1 \cdot s( t - \tau_1)\hspace{0.05cm}.</math>
 
::<math>r(t) = r_1(t) + k_0 \cdot r_1( t - \tau_0) \hspace{0.5cm}{\rm with} \hspace{0.5cm} r_1(t) = k_1 \cdot s( t - \tau_1)\hspace{0.05cm}.</math>
  
The graphic illustrates the equation.&nbsp; With the following simplifications&nbsp; $k_1 = 1$&nbsp; and&nbsp; $\tau_1 = 0$&nbsp; &nbsp; &#8658; &nbsp; $r_1(t) = s(t)$&nbsp; we obtain:
+
The figure illustrates the equation.&nbsp; With the simplifications&nbsp; $k_1 = 1$&nbsp; and&nbsp; $\tau_1 = 0$&nbsp; &nbsp; &#8658; &nbsp; $r_1(t) = s(t)$&nbsp; we obtain:
  
 
::<math>r(t) = s(t) + k_0 \cdot s( t - \tau_0) \hspace{0.05cm}.</math>
 
::<math>r(t) = s(t) + k_0 \cdot s( t - \tau_0) \hspace{0.05cm}.</math>
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From this simplified model&nbsp; (without the grey-shaded block)&nbsp; important descriptive variables can be easily calculated:
 
From this simplified model&nbsp; (without the grey-shaded block)&nbsp; important descriptive variables can be easily calculated:
 
*If you use the&nbsp;  [[Signal_Representation/Fourier_Transform_Laws#Verschiebungssatz| Displacement Law]]&nbsp; you get the transfer function
 
*If you use the&nbsp;  [[Signal_Representation/Fourier_Transform_Laws#Verschiebungssatz| Displacement Law]]&nbsp; you get the transfer function
 
  
 
::<math>H(f) = {R(f)}/{S(f)} = 1 + k_0 \cdot {\rm e}^{  - {\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi f \hspace{0.05cm} \cdot \hspace{0.05cm} \tau_0} \hspace{0.05cm}.</math>
 
::<math>H(f) = {R(f)}/{S(f)} = 1 + k_0 \cdot {\rm e}^{  - {\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi f \hspace{0.05cm} \cdot \hspace{0.05cm} \tau_0} \hspace{0.05cm}.</math>
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[[File:Mob_T_2_2_S1c_neu.png|right|frame|Absolute value of the transfer function of a two-way channel &nbsp; $(\tau_0 = 2 \ \rm &micro; s)$]]
 
[[File:Mob_T_2_2_S1c_neu.png|right|frame|Absolute value of the transfer function of a two-way channel &nbsp; $(\tau_0 = 2 \ \rm &micro; s)$]]
  
 
+
The graph shows the transfer function in terms of its absolute value in the range&nbsp; $\pm 1 \ \rm MHz$.&nbsp; You can see from this representation:
The graph shows the transfer function in terms of its absolute value in the range&nbsp; $\pm 1 \ \rm MHz$.  
 
 
 
You can see from this representation:
 
  
 
*The transfer function&nbsp; $H(f)$&nbsp; and also its absolute value is periodic with&nbsp; $1/\tau_0 = 500 \ \rm kHz$.
 
*The transfer function&nbsp; $H(f)$&nbsp; and also its absolute value is periodic with&nbsp; $1/\tau_0 = 500 \ \rm kHz$.
 
   
 
   
 +
*This frequency period here is also the&nbsp; [[Mobile_Communications/The GWSSUS channel model#Parameters of the GWSSUS model|coherence bandwidth]] .<br>
  
*This frequency period here is also the&nbsp; [[Mobile_Communications/The GWSSUS channel model#Parameters of the GWSSUS model|Coherence Bandwidth]] .<br>
+
*The fluctuations around the mean value&nbsp; $\vert H(f) \vert = 1$&nbsp; are the stronger, the larger the&nbsp; (relative)&nbsp; contribution&nbsp; $k_0$&nbsp; of the second path is&nbsp; (i.e. the echo).}}<br>
 
 
 
 
*The fluctuations around the mean value&nbsp; $\vert H(f) \vert = 1$&nbsp; are the stronger, the larger the&nbsp; (relative)&nbsp; contribution&nbsp; $k_0$&nbsp; of the secondary path&nbsp; (i.e. the echo)&nbsp; is.}}<br>
 
  
 
== Coherence bandwidth as a function of ''M'' ==
 
== Coherence bandwidth as a function of ''M'' ==
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We are now modifying the two-way model in such a way that we allow more than two paths, as is the case for mobile communications.
 
We are now modifying the two-way model in such a way that we allow more than two paths, as is the case for mobile communications.
  
[[File:P ID2149 Mob T 2 2 S2a v1.png|right|frame|Frequency Response at&nbsp; $M = 2$&nbsp; (blue) and&nbsp; $M = 3$&nbsp; (red) |class=fit]]
+
[[File:P ID2149 Mob T 2 2 S2a v1.png|right|frame|Frequency response at&nbsp; $M = 2$&nbsp; (blue) and&nbsp; $M = 3$&nbsp; (red) |class=fit]]
 
In general, the multipath channel model is thus:
 
In general, the multipath channel model is thus:
  
:$$ = \sum_{m = 1}^{M}\hspace{0.15cm} k_m \cdot s( t - \tau_m)  
+
:$$ r(t)= \sum_{m = 1}^{M}\hspace{0.15cm} k_m \cdot s( t - \tau_m)$$
  \hspace{0.3cm}\Rightarrow \hspace{0.3cm} h(\tau) = \sum_{m = 1}^{M}\hspace{0.15cm} k_m \cdot \delta( \tau - \tau_m)
+
   
 +
:$$\Rightarrow \hspace{0.3cm} h(\tau) = \sum_{m = 1}^{M}\hspace{0.15cm} k_m \cdot \delta( \tau - \tau_m)
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
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:$$\tau_1 = 1\,\,{\rm &micro; s}\hspace{0.05cm}, \hspace{0.2cm} k_1 = 0.8\hspace{0.05cm}, \hspace{0.2cm}
 
:$$\tau_1 = 1\,\,{\rm &micro; s}\hspace{0.05cm}, \hspace{0.2cm} k_1 = 0.8\hspace{0.05cm}, \hspace{0.2cm}
  \tau_2 = 3\,\,{\rm &micro; s}\hspace{0.05cm}, \hspace{0.2cm} k_2 \approx 0.43\hspace{0.05cm}, $$
+
  \tau_2 = 3\,\,{\rm &micro; s}\hspace{0.05cm}, \hspace{0.2cm} k_2 \approx 0.43\hspace{0.05cm}, \hspace{0.2cm} \tau_3 = 9\,\,{\rm &micro; s}\hspace{0.05cm}, \hspace{0.2cm} k_3 \approx 0.43
:$$ \tau_3 = 9\,\,{\rm &micro; s}\hspace{0.05cm}, \hspace{0.2cm} k_3 \approx 0.43
 
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
 
With the selected constants, both channels have the root mean square value&nbsp; ${\rm E}\big [k_m^2\big ] = 1$&nbsp;.
 
With the selected constants, both channels have the root mean square value&nbsp; ${\rm E}\big [k_m^2\big ] = 1$&nbsp;.
  
 +
The graph shows the magnitude functions&nbsp; $ |H(f)|$&nbsp; of both channels and the corresponding impulse responses&nbsp; $h(\tau)$.&nbsp; One can see from these graphs:
 +
*In the blue channel&nbsp; $(M = 2)$&nbsp; the Dirac functions occur in a range of width&nbsp; $\Delta \tau_{\rm max} = 2 \ \rm &micro; s$. &nbsp;
 +
*With the red channel&nbsp; $(M = 3)$&nbsp; this value is four times as large: &nbsp; $\Delta \tau_{\rm max} = 8 \ \rm &micro; s$.<br>
  
The graph shows the magnitude functions&nbsp; $ |H(f)|$&nbsp; of both channels and the corresponding impulse responses&nbsp; $h(\tau)$.&nbsp; One can see from these graphs
+
*As a first approximation for&nbsp; [[Mobile_Communications/The GWSSUS channel model#Parameters of the GWSSUS model|coherence bandwidth]]&nbsp; $B_{\rm K}\hspace{0.01cm}'\approx 1/ \Delta \tau_{\rm max}$ is often used, which may differ from the correct value by a factor of&nbsp; $2$&nbsp; or more.&nbsp;  
*In the blue channel&nbsp; $(M = 2)$&nbsp; the Dirac functions occur in a range of width&nbsp; $\Delta \tau_{\rm max} = 2 \ \rm &micro; s$. &nbsp; With the red channel&nbsp; $(M = 3)$&nbsp; this value is four times as large: &nbsp; $\Delta \tau_{\rm max} = 8 \ \rm &micro; s$.<br>
+
*This simple approximation, marked with an apostrophe, results for the blue channel to&nbsp; $B_{\rm K}\hspace{0.01cm}'= 500 \ \rm kHz$.
 
+
* For the red channel it is&nbsp; $B_{\rm K}\hspace{0.01cm}'= 125 \ \rm kHz$&nbsp; which is just one fourth of the blue channel's.<br>
*As a first approximation for the yet to be defined&nbsp; [[Mobile_Communications/The GWSSUS channel model#Parameters of the GWSSUS model|Coherence Bandwidth]]&nbsp; $B_{\rm K}$&nbsp; &nbsp; $1/ \Delta \tau_{\rm max}$ is often used, which may differ from the correct value by a factor of&nbsp; $2$&nbsp; or more.&nbsp;  
 
*This simple approximation, marked with an apostrophe, results for the blue channel to&nbsp; $B_{\rm K}\hspace{0.01cm}'= 500 \ \rm kHz$, for the red channel it is&nbsp; $B_{\rm K}\hspace{0.01cm}'= 125 \ \rm kHz$&nbsp; which is just one fourth of the blue channel's<br>
 
  
  
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
$\text{In general the following applies: $&nbsp
+
$\text{In general the following applies:} $
#&nbsp; If the signal bandwidth&nbsp; $B_{\rm S} = 1/T_{\rm S}$&nbsp; is much smaller than the coherence bandwidth&nbsp; $B_{\rm K}$, then the channel for this system can be considered <i>non-frequency selective</i>&nbsp;&nbsp; &nbsp;$(T_{\rm S}$&nbsp; denotes the symbol duration$)$.<br>
+
#&nbsp; If the signal bandwidth&nbsp; $B_{\rm S} = 1/T_{\rm S}$&nbsp; is much smaller than the coherence bandwidth&nbsp; $B_{\rm K}$, then the channel can be considered as <i>non-frequency selective</i>&nbsp;&nbsp; &nbsp;<br>$(T_{\rm S}$&nbsp; denotes the symbol duration$)$.<br>
 
#&nbsp; In other words: &nbsp; For a given&nbsp; $B_{\rm S}$&nbsp; the smaller the coherence bandwidth&nbsp; $B_{\rm K}$&nbsp; or the larger the maximum delay&nbsp; $\Delta \tau_{\rm max}$&nbsp; the greater the frequency selectivity.
 
#&nbsp; In other words: &nbsp; For a given&nbsp; $B_{\rm S}$&nbsp; the smaller the coherence bandwidth&nbsp; $B_{\rm K}$&nbsp; or the larger the maximum delay&nbsp; $\Delta \tau_{\rm max}$&nbsp; the greater the frequency selectivity.
#&nbsp; This also means: &nbsp; The frequency selectivity is often determined by the longest echo.#&nbsp; Many short echoes with a total energy&nbsp; $E$&nbsp; are less disturbing than a long echo of the same energy&nbsp; $E$.<br>}}
+
#&nbsp; This also means: &nbsp; The frequency selectivity is often determined by the longest echo.
 +
#&nbsp; Many short echoes with a total energy&nbsp; $E$&nbsp; are less disturbing than one long echo of the same energy&nbsp; $E$.<br>}}
  
 
== Consideration of the time variance ==
 
== Consideration of the time variance ==
 
<br>
 
<br>
Up to now the attenuation factors&nbsp; $k_m$&nbsp; were assumed to be constant. For mobile radio, however, this channel model is only correct if transmitter and receiver are static, which is merely a special case for this communication system.
+
Up to now the attenuation factors&nbsp; $k_m$&nbsp; were assumed to be constant.&nbsp; For mobile radio, however, this channel model is only correct if transmitter and receiver are static, which is merely a special case for this communication system.
  
 
For a moving user, these constant factors&nbsp; $k_m$&nbsp; must be replaced by the time-variant factors&nbsp; $z_m(t)$&nbsp; which are each based on random processes. You should note this:
 
For a moving user, these constant factors&nbsp; $k_m$&nbsp; must be replaced by the time-variant factors&nbsp; $z_m(t)$&nbsp; which are each based on random processes. You should note this:
*The magnitudes of the complex weighting factors&nbsp; $z_m(t)$&nbsp; are rayleighly distributed according to the page&nbsp; [[Mobile_Communications/Probability density of Rayleigh fading#Sample signal characteristics with Rayleigh fading|Signal characteristics with Rayleigh fading]]&nbsp; or &ndash; with line-of-sight connection &ndash; Rice distributed, as described in&nbsp; [[Mobile_Communications/Non-frequency selective fading with direct component#Example of signal behaviour with Rice fading|Signal characteristics with Rice fading]]&nbsp;.<br>
+
[[File:P ID3104 Mob T 2 2 S2b v1.png|right|frame|Mobile channel model considering time variance and echoes|class=fit]]
  
*The bonds within the process&nbsp; $z_m(t)$&nbsp; are related to the mobility properties (speed, direction, etc.) to the&nbsp; [[Mobile_Communications/Statistical bonds within the Rayleigh process#ACF und PDS with Rayleigh-Fading|Jakes&ndash;Spectrum]]&nbsp;.<br><br>
+
*The magnitudes of the complex weighting factors&nbsp; $z_m(t)$&nbsp; are Rayleigh distributed according to the page&nbsp; [[Mobile_Communications/Probability density of Rayleigh fading#Sample signal characteristics with Rayleigh fading|Signal characteristics with Rayleigh fading]]&nbsp; or &ndash; with line-of-sight connection &ndash; Rice distributed, as described in&nbsp; [[Mobile_Communications/Non-frequency selective fading with direct component#Example of signal behaviour with Rice fading|Signal characteristics with Rice fading]]&nbsp;.<br>
  
[[File:P ID3104 Mob T 2 2 S2b v1.png|right|frame|mobile channel model considering time variance and echoes|class=fit]]
+
*The bindings within the process&nbsp; $z_m(t)$&nbsp; are related to the mobility properties&nbsp; (speed, direction, etc.)&nbsp; to the&nbsp; [[Mobile_Communications/Statistical bonds within the Rayleigh process#ACF und PDS with Rayleigh-Fading|Jakes Spectrum]]&nbsp;.<br><br>
The diagram shows the generally valid model for the mobile communications channel.&nbsp; "Generally valid" but only with reservations, as explained at the end of the page.  
+
 
 +
The figure shows the generally valid model for the mobile communications channel.&nbsp; "Generally valid" but only with reservations, as explained at the end of&nbsp; $\text{Example 2}$.  
  
 
For an understanding of the figure we refer to the chapter&nbsp; [[Mobile_Communications/Probability density of Rayleigh fading#A very general description of the mobile communication channel|General description of the mobile communications channel]]. Please note:  
 
For an understanding of the figure we refer to the chapter&nbsp; [[Mobile_Communications/Probability density of Rayleigh fading#A very general description of the mobile communication channel|General description of the mobile communications channel]]. Please note:  
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Two different views are shown:
 
Two different views are shown:
 
*The left image shows&nbsp; $h(\tau,\hspace{0.1cm} t)$&nbsp; as a function of the delay time&nbsp; $\tau$&nbsp; at a fixed time&nbsp; $t$.  
 
*The left image shows&nbsp; $h(\tau,\hspace{0.1cm} t)$&nbsp; as a function of the delay time&nbsp; $\tau$&nbsp; at a fixed time&nbsp; $t$.  
*The viewing direction in the right image is rotated by&nbsp; $90^\circ$&nbsp;.  
+
*The viewing direction in the right image is rotated by&nbsp; $90^\circ$&nbsp;.&nbsp; By using the color coding, the representation should be understandable.<br>
*By using the color coding, the representation should be understandable.<br>
 
 
<br clear=all>
 
<br clear=all>
This picture also shows the weak point of our mobile communications channel model: &nbsp; Although the coefficients&nbsp; $z_m(t)$&nbsp; are variable, the delay times&nbsp; $\tau_m$&nbsp; are fixed. &nbsp; This does not correspond to reality, if the mobile station is moving and the connection takes place in a changing environment.&nbsp; &nbsp; $\tau_m(t)$&nbsp; should be considered.}}<br>
+
This geaphic also shows the weak point of our mobile communications channel model: &nbsp; Although the coefficients&nbsp; $z_m(t)$&nbsp; are variable, the delay times&nbsp; $\tau_m$&nbsp; are fixed. &nbsp; This does not correspond to reality, if the mobile station is moving and the connection takes place in a changing environment.&nbsp; &nbsp; $\tau_m(t)$&nbsp; should be considered.}}<br>
 +
 
  
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
$\text{Conclusion:}$&nbsp; It is helpful to make a slight modification to the above model:
+
$\text{Conclusion:}$&nbsp;
 +
It is helpful to make a slight modification to the above model:  
 
[[File:P ID2153 Mob T 2 2 S2d v2.png|right|frame|General model of the mobile channel|class=fit]]
 
[[File:P ID2153 Mob T 2 2 S2d v2.png|right|frame|General model of the mobile channel|class=fit]]
*One chooses the number&nbsp; $M'$&nbsp; of (possible) main paths much larger than necessary and sets&nbsp; $\tau_m = m \cdot \delta \tau$.  
+
 
*The incremental&nbsp; (minimum resolvable)&nbsp; delay&nbsp; $\Delta \tau = T_{\rm S}$&nbsp; results from the sampling rate and thus also from the bandwidth&nbsp; $B_{\rm S} = 1/T_{\rm S}$&nbsp; of the transmitted signal.<br>
+
*One chooses the number&nbsp; $M'$&nbsp; of (possible) main paths much larger than necessary and sets&nbsp; $\tau_m = m \cdot \Delta \tau$.  
*The maximum delay time&nbsp; $\tau_\text{max} = M' \cdot \delta \tau$&nbsp; of this model is equal to the inverse of the coherence bandwidth&nbsp; $B_{\rm K}$.  
+
*The incremental&nbsp; (minimum resolvable)&nbsp; delay&nbsp; $\Delta \tau = T_{\rm S}$&nbsp; results from the sampling rate and thus from the bandwidth&nbsp; $B_{\rm S} = 1/T_{\rm S}$&nbsp; of the signal&nbsp; $s(t)$.<br>
*The number of paths considered is thus&nbsp; $M' = B_{\rm S}/B_{\rm K}$.
+
*The maximum delay time&nbsp; $\tau_\text{max} = M' \cdot \Delta \tau$&nbsp; of this model is equal to the inverse of the coherence bandwidth&nbsp; $B_{\rm K}$.&nbsp; The number of paths considered is thus&nbsp; $M' = B_{\rm S}/B_{\rm K}$.
<br clear=all>
+
 
 +
 
 
Here, too, usually no more than&nbsp; $M = 5$&nbsp; main paths simultaneously provide a relevant contribution to the impulse response.  
 
Here, too, usually no more than&nbsp; $M = 5$&nbsp; main paths simultaneously provide a relevant contribution to the impulse response.  
 
*The advantage over the first model is that for the delays now all values&nbsp; $\tau_m \le \tau_\text{max}$&nbsp; are possible, with a temporal resolution of&nbsp; $\Delta \tau$&nbsp;.  
 
*The advantage over the first model is that for the delays now all values&nbsp; $\tau_m \le \tau_\text{max}$&nbsp; are possible, with a temporal resolution of&nbsp; $\Delta \tau$&nbsp;.  
*Am&nbsp; [[Mobile_Communications/The GWSSUS channel model#Simulation according to the GWSSUS model|End of GWSSUS chapter]]&nbsp; we will come back to this general model again.<br>}}
+
*At the end of next chapter&nbsp; [[Mobile_Communications/The GWSSUS channel model#Simulation according to the GWSSUS model|The GWSSUS channel model]]&nbsp; we will come back to this general model again.<br>}}
  
 
==Exercises to chapter==
 
==Exercises to chapter==

Revision as of 18:20, 10 January 2021

Time invariant description of the two-way channel


We assume the scenario shown in the graph.  This assumes

Time–invariant consideration of the two-way channel
  • Transmitter and receiver are  at rest
    Then both the channel transfer function and the impulse response are time–independent.  For all times  $t$  applies  $H(f, \hspace{0.05cm}t) = H(f)$  and  $h(\tau, \hspace{0.05cm}t) = h(\tau)$.
  • two-way channel:  
    The transmission signal  $s(t)$  reaches the receiver on a direct path with the path length  $d_1$,  and there is also an echo due to the reflective ground  $($the total path length is  $d_2)$.


Thus, the following applies to the received signal:

\[r(t) = r_1(t) + r_2(t) = k_1 \cdot s( t - \tau_1) + k_2 \cdot s( t - \tau_2) \hspace{0.05cm}.\]


The following statements should be noted:

  • Compared to the transmission signal, the signal  $r_1(t)$  received via the direct path is attenuated by the factor  $k_1$  and delayed by   $\tau_1$ .
  • The attenuation factor  $k_1$  is calculated with the  path loss model.  The greater the transmission frequency  $f_{\rm S}$,  the distance  $d_1$  and the exponent  $\gamma$  are, the smaller is   $k_1$  and thus the greater is the loss.
  • The delay  $\tau_1 = d_1/c$  increases proportionally with the path length  $d_1$ .   For example, for the distance  $d_1 = 3 \ \rm km$  and the speed of light  $c = 3 \cdot 10^8 \ \rm m/s$  the delay will be  $\tau_1 = 10 \ \rm µ s$.
  • Because of the larger path length  $(d_2 > d_1)$  the second path has a greater attenuation   ⇒   smaller pre-factor   ⇒   $(|k_2| < |k_1|)$  and accordingly also a greater delay   $(\tau_2 > \tau_1)$.
  • In addition, it must be taken into account that the reflection from buildings or the ground leads to a phase rotation of  $\pi \ (180^\circ)$.  This causes the factor  $k_2$  to become negative.  In the following, however, the negative sign of  $k_2$  is ignored.

Note:   We refer here to the applet  Effects of multi–path reception.


Simple time–invariant model of the two-way channel


Simple model for the two-way channel

For the frequency selectivity

  • the path loss  $($marked by  $k_1)$  and
  • the basic term  $\tau_1$ 


are irrelevant. The only decisive factors here are path loss differences and runtime differences.

We will now describe the two-way channel with the new parameters 

$$k_0 = |k_2 /k_1 |,\hspace{0.5cm} \tau_0 = \tau_2 - \tau_1.$$

This results in:

\[r(t) = r_1(t) + k_0 \cdot r_1( t - \tau_0) \hspace{0.5cm}{\rm with} \hspace{0.5cm} r_1(t) = k_1 \cdot s( t - \tau_1)\hspace{0.05cm}.\]

The figure illustrates the equation.  With the simplifications  $k_1 = 1$  and  $\tau_1 = 0$    ⇒   $r_1(t) = s(t)$  we obtain:

\[r(t) = s(t) + k_0 \cdot s( t - \tau_0) \hspace{0.05cm}.\]

From this simplified model  (without the grey-shaded block)  important descriptive variables can be easily calculated:

\[H(f) = {R(f)}/{S(f)} = 1 + k_0 \cdot {\rm e}^{ - {\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi f \hspace{0.05cm} \cdot \hspace{0.05cm} \tau_0} \hspace{0.05cm}.\]
\[h(\tau) = 1 + k_0 \cdot \delta(\tau - \tau_0) \hspace{0.05cm}.\]

$\text{Example 1:}$  We consider a two-way channel with delay   $\tau_0 = 2 \ \ \rm µ s$  and some attenuation factors  $k_0$  between  $0$  and  $1$.

Absolute value of the transfer function of a two-way channel   $(\tau_0 = 2 \ \rm µ s)$

The graph shows the transfer function in terms of its absolute value in the range  $\pm 1 \ \rm MHz$.  You can see from this representation:

  • The transfer function  $H(f)$  and also its absolute value is periodic with  $1/\tau_0 = 500 \ \rm kHz$.
  • The fluctuations around the mean value  $\vert H(f) \vert = 1$  are the stronger, the larger the  (relative)  contribution  $k_0$  of the second path is  (i.e. the echo).


Coherence bandwidth as a function of M


We are now modifying the two-way model in such a way that we allow more than two paths, as is the case for mobile communications.

Frequency response at  $M = 2$  (blue) and  $M = 3$  (red)

In general, the multipath channel model is thus:

$$ r(t)= \sum_{m = 1}^{M}\hspace{0.15cm} k_m \cdot s( t - \tau_m)$$
$$\Rightarrow \hspace{0.3cm} h(\tau) = \sum_{m = 1}^{M}\hspace{0.15cm} k_m \cdot \delta( \tau - \tau_m) \hspace{0.05cm}.$$

We now compare

  • the two-way channel  $(M = 2)$  with the parameters
\[\tau_1 = 1\,\,{\rm µ s}\hspace{0.05cm}, \hspace{0.2cm} k_1 = 0.8\hspace{0.05cm}, \hspace{0.2cm} \tau_2 = 3\,\,{\rm µ s}\hspace{0.05cm}, \hspace{0.2cm} k_2 = 0.6\]
  • and the following three-way channel  $(M = 3)$:
$$\tau_1 = 1\,\,{\rm µ s}\hspace{0.05cm}, \hspace{0.2cm} k_1 = 0.8\hspace{0.05cm}, \hspace{0.2cm} \tau_2 = 3\,\,{\rm µ s}\hspace{0.05cm}, \hspace{0.2cm} k_2 \approx 0.43\hspace{0.05cm}, \hspace{0.2cm} \tau_3 = 9\,\,{\rm µ s}\hspace{0.05cm}, \hspace{0.2cm} k_3 \approx 0.43 \hspace{0.05cm}.$$

With the selected constants, both channels have the root mean square value  ${\rm E}\big [k_m^2\big ] = 1$ .

The graph shows the magnitude functions  $ |H(f)|$  of both channels and the corresponding impulse responses  $h(\tau)$.  One can see from these graphs:

  • In the blue channel  $(M = 2)$  the Dirac functions occur in a range of width  $\Delta \tau_{\rm max} = 2 \ \rm µ s$.  
  • With the red channel  $(M = 3)$  this value is four times as large:   $\Delta \tau_{\rm max} = 8 \ \rm µ s$.
  • As a first approximation for  coherence bandwidth  $B_{\rm K}\hspace{0.01cm}'\approx 1/ \Delta \tau_{\rm max}$ is often used, which may differ from the correct value by a factor of  $2$  or more. 
  • This simple approximation, marked with an apostrophe, results for the blue channel to  $B_{\rm K}\hspace{0.01cm}'= 500 \ \rm kHz$.
  • For the red channel it is  $B_{\rm K}\hspace{0.01cm}'= 125 \ \rm kHz$  which is just one fourth of the blue channel's.


$\text{In general the following applies:} $

  1.   If the signal bandwidth  $B_{\rm S} = 1/T_{\rm S}$  is much smaller than the coherence bandwidth  $B_{\rm K}$, then the channel can be considered as non-frequency selective    
    $(T_{\rm S}$  denotes the symbol duration$)$.
  2.   In other words:   For a given  $B_{\rm S}$  the smaller the coherence bandwidth  $B_{\rm K}$  or the larger the maximum delay  $\Delta \tau_{\rm max}$  the greater the frequency selectivity.
  3.   This also means:   The frequency selectivity is often determined by the longest echo.
  4.   Many short echoes with a total energy  $E$  are less disturbing than one long echo of the same energy  $E$.

Consideration of the time variance


Up to now the attenuation factors  $k_m$  were assumed to be constant.  For mobile radio, however, this channel model is only correct if transmitter and receiver are static, which is merely a special case for this communication system.

For a moving user, these constant factors  $k_m$  must be replaced by the time-variant factors  $z_m(t)$  which are each based on random processes. You should note this:

Mobile channel model considering time variance and echoes
  • The bindings within the process  $z_m(t)$  are related to the mobility properties  (speed, direction, etc.)  to the  Jakes Spectrum .

The figure shows the generally valid model for the mobile communications channel.  "Generally valid" but only with reservations, as explained at the end of  $\text{Example 2}$.

For an understanding of the figure we refer to the chapter  General description of the mobile communications channel. Please note:

  • The  $M$  main paths are characterized by large propagation time differences.
  • The time-variant complex coefficients  $z_m(t)$  result from the sum of many secondary paths whose delay times are all approximately the same  $\tau_m$ .


$\text{Example 2:}$  Studies have shown that in mobile communications no more than four or five main pathways are effective at the same time.

2D-Impulse response with  $M = 3$  paths

The represented 2D–impulse response  $h(\tau,\hspace{0.1cm} t)$  applies to  $M = 3$  main paths with time-variant behavior, where the received power decreases with increasing delay in the statistical average.  For this graph the above sketched channel model is used as a basis.

Two different views are shown:

  • The left image shows  $h(\tau,\hspace{0.1cm} t)$  as a function of the delay time  $\tau$  at a fixed time  $t$.
  • The viewing direction in the right image is rotated by  $90^\circ$ .  By using the color coding, the representation should be understandable.


This geaphic also shows the weak point of our mobile communications channel model:   Although the coefficients  $z_m(t)$  are variable, the delay times  $\tau_m$  are fixed.   This does not correspond to reality, if the mobile station is moving and the connection takes place in a changing environment.    $\tau_m(t)$  should be considered.



$\text{Conclusion:}$  It is helpful to make a slight modification to the above model:

General model of the mobile channel
  • One chooses the number  $M'$  of (possible) main paths much larger than necessary and sets  $\tau_m = m \cdot \Delta \tau$.
  • The incremental  (minimum resolvable)  delay  $\Delta \tau = T_{\rm S}$  results from the sampling rate and thus from the bandwidth  $B_{\rm S} = 1/T_{\rm S}$  of the signal  $s(t)$.
  • The maximum delay time  $\tau_\text{max} = M' \cdot \Delta \tau$  of this model is equal to the inverse of the coherence bandwidth  $B_{\rm K}$.  The number of paths considered is thus  $M' = B_{\rm S}/B_{\rm K}$.


Here, too, usually no more than  $M = 5$  main paths simultaneously provide a relevant contribution to the impulse response.

  • The advantage over the first model is that for the delays now all values  $\tau_m \le \tau_\text{max}$  are possible, with a temporal resolution of  $\Delta \tau$ .
  • At the end of next chapter  The GWSSUS channel model  we will come back to this general model again.

Exercises to chapter


Exercise 2.2: Simple Two-Path Channel Model

Exercise 2.2Z: Real Two-Path Channel

Exercise 2.3: Yet Another Multi-Path Channel

Exercise 2.4: 2-D Transfer Function