Difference between revisions of "Aufgaben:Exercise 5.2Z: About PN Modulation"

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[[File:P_ID1871__Mod_Z_5_2.png|right|frame|Models of PN modulation (top) and BPSK (bottom)]]
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[[File:EN_Bei_A_4_5.png|right|frame|Models of PN modulation (top) and BPSK (bottom)]]
The diagram shows the equivalent circuit of  $\rm PN$ modulation  $($Direct Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range, based on AWGN noise  $n(t)$.  Shown below is the low-pass model of binary phase modulation  $\rm (BPSK)$.
+
The upper diagram shows the equivalent circuit of  $\rm PN$  modulation  $($Direct-Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range,  based on AWGN noise  $n(t)$.   
  
The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
+
Shown below is the low-pass model of binary phase shift keying  $\rm (BPSK)$. 
 +
*The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
  
The function of the integrator can be described as follows:
+
*The function of the integrator can be described as follows:
 
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
 
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
  
The two models differ by multiplication with the  $±1$ spread signal  $c(t)$  at transmitter and receiver, where only the degree of spread  $J$  is known from  $c(t)$. 
+
*The two models differ by multiplication with the  $±1$ spreading signal  $c(t)$  at transmitter and receiver,  where only the spreading factor  $J$  is known from  $c(t)$. 
 +
 
  
 
It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability
 
It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability
 
:$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$
 
:$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$
is also valid for PN modulation, or how the given equation should be modified.
+
is also valid for PN modulation,  or how the given equation should be modified.
  
  
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 +
Notes:
 +
*This exercise belongs to the chapter  [[Modulation_Methods/Direct-Sequence_Spread_Spectrum_Modulation|Direct-Sequence Spread Spectrum Modulation]].
  
 
+
*For the solution of this exercise,  the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.
 
 
''Notes:''
 
*This exercise belongs to the chapter  [[Modulation_Methods/Direct-Sequence_Spread_Spectrum_Modulation|Direct-Sequence Spread Spectrum Modulation]].
 
*For the solution of this exercise, the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.
 
 
   
 
   
  
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<quiz display=simple>
 
<quiz display=simple>
{Which detection signal values are possible with BPSK (in the noise-free case)?
+
{Which detection signal values are possible with BPSK&nbsp; (in the noise-free case)?
 
|type="[]"}
 
|type="[]"}
 
- $d(νT)$&nbsp; can be Gaussian distributed.
 
- $d(νT)$&nbsp; can be Gaussian distributed.
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+ Only the values &nbsp;$d(νT) = +1$&nbsp; and &nbsp;$d(νT) = -1$&nbsp; are possible.
 
+ Only the values &nbsp;$d(νT) = +1$&nbsp; and &nbsp;$d(νT) = -1$&nbsp; are possible.
  
{Which values are possible in PN modulation (in the noise-free) case?
+
{Which values are possible in PN modulation&nbsp; (in the noise-free)&nbsp; case?
 
|type="[]"}
 
|type="[]"}
 
- $d(νT)$&nbsp; can be Gaussian distributed.
 
- $d(νT)$&nbsp; can be Gaussian distributed.
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- The noise power &nbsp;$σ_n^2$&nbsp; must be reduced by a factor of &nbsp;$J$.&nbsp;  
 
- The noise power &nbsp;$σ_n^2$&nbsp; must be reduced by a factor of &nbsp;$J$.&nbsp;  
  
{What is the bit error probability &nbsp;$p_{\rm B}$&nbsp; for &nbsp;$10 \lg \  (E_{\rm B}/N_0) = 6\ \rm  dB$&nbsp; for PN modulation?&nbsp; ''Note:'' &nbsp; For BPSK, the following applies in this case: &nbsp; $p_{\rm B} ≈ 2.3 · 10^{–3}$.
+
{What is the bit error probability &nbsp;$p_{\rm B}$&nbsp; for &nbsp;$10 \lg \  (E_{\rm B}/N_0) = 6\ \rm  dB$&nbsp; for PN modulation?&nbsp; <br>Note: &nbsp; For BPSK, the following applies in this case: &nbsp; $p_{\rm B} ≈ 2.3 · 10^{–3}$.
 
|type="()"}
 
|type="()"}
 
- The larger &nbsp;$J$&nbsp; is chosen, the smaller &nbsp;$p_{\rm B}$ is.
 
- The larger &nbsp;$J$&nbsp; is chosen, the smaller &nbsp;$p_{\rm B}$ is.
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; The <u>last solution</u> is correct:
+
'''(1)'''&nbsp; The&nbsp; <u>last solution</u>&nbsp; is correct:
 
*We are dealing here with an optimal receiver.
 
*We are dealing here with an optimal receiver.
*Without noise, the signal&nbsp; $b(t)$&nbsp; within each bit is constantly equal to&nbsp; $+1$&nbsp; or&nbsp; $-1$.  
+
*Without noise,&nbsp; the signal&nbsp; $b(t)$&nbsp; within each bit is constantly equal to&nbsp; $+1$&nbsp; or&nbsp; $-1$.  
 
*From the given equation for the integrator
 
*From the given equation for the integrator
 
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
 
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
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'''(2)'''&nbsp; Again the <u>last solution</u> is correct:
+
'''(2)'''&nbsp; Again the&nbsp; <u>last solution</u>&nbsp; is correct:
* In the noise&ndash; and interference-free case &nbsp; ⇒ &nbsp; $n(t) = 0$,&nbsp; the twofold multiplication by&nbsp; $c(t) ∈ \{+1, –1\}$&nbsp; can be omitted,
+
* In the noise-free and interference-free case &nbsp; ⇒ &nbsp; $n(t) = 0$,&nbsp; the twofold multiplication by&nbsp; $c(t) ∈ \{+1, –1\}$&nbsp; can be omitted,
 
*so that the upper model is identical to the lower model.
 
*so that the upper model is identical to the lower model.
  
  
  
'''(3)'''&nbsp; <u>Solution 1</u> is correct:
+
'''(3)'''&nbsp; <u>Solution 1</u>&nbsp; is correct:
*Since both models are identical in the noise-free case, only the noise signal has to be adjusted: &nbsp; $n'(t) = n(t) · c(t)$.  
+
*Since both models are identical in the noise-free case,&nbsp; only the noise signal has to be adjusted: &nbsp; $n'(t) = n(t) · c(t)$.  
*In contrast, the other two solutions are not applicable:
+
*In contrast,&nbsp; the other two solutions are not applicable:
 
*The integration must still be done over&nbsp; $T = J · T_c$&nbsp; and the PN modulation does not reduce the AWGN noise.
 
*The integration must still be done over&nbsp; $T = J · T_c$&nbsp; and the PN modulation does not reduce the AWGN noise.
  
  
  
'''(4)'''&nbsp; The <u>last solution</u> is correct:
+
'''(4)'''&nbsp; The&nbsp; <u>last solution</u>&nbsp; is correct:
*Multiplying the AWGN noise by the high-frequency&nbsp; $±1$ signal&nbsp; $c(t)$, the product is also Gaussian and white.
+
*Multiplying the AWGN noise by the high-frequency&nbsp; $±1$ signal&nbsp; $c(t)$,&nbsp; the product is also Gaussian and white.
*Because of &nbsp;${\rm E}\big[c^2(t)\big] = 1$,&nbsp; the noise variance is not changed either.
+
*Because of &nbsp;${\rm E}\big[c^2(t)\big] = 1$,&nbsp; the noise variance is not changed either.&nbsp; Thus:                                                           
*Thus, the equation&nbsp; $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$&nbsp; valid for BPSK is also applicable for PN modulation, independent of the spreading factor&nbsp; $J$&nbsp; and the specific spreading sequence.
+
*The equation&nbsp; $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$&nbsp; valid for BPSK is also applicable for PN modulation,&nbsp; independent of spreading factor&nbsp; $J$&nbsp; and specific spreading sequence.
*Ergo: &nbsp; &nbsp; For AWGN noise, band spreading neither increases nor decreases the error probability.
+
*Ergo:&nbsp; For AWGN noise,&nbsp; band spreading neither increases nor decreases the error probability.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  

Latest revision as of 18:55, 4 March 2023

Models of PN modulation (top) and BPSK (bottom)

The upper diagram shows the equivalent circuit of  $\rm PN$  modulation  $($Direct-Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range,  based on AWGN noise  $n(t)$. 

Shown below is the low-pass model of binary phase shift keying  $\rm (BPSK)$. 

  • The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
  • The function of the integrator can be described as follows:
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
  • The two models differ by multiplication with the  $±1$ spreading signal  $c(t)$  at transmitter and receiver,  where only the spreading factor  $J$  is known from  $c(t)$. 


It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability

$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$

is also valid for PN modulation,  or how the given equation should be modified.



Notes:

  • For the solution of this exercise,  the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.


Questions

1

Which detection signal values are possible with BPSK  (in the noise-free case)?

$d(νT)$  can be Gaussian distributed.
$d(νT)$  can take the values  $+1$,  $0$  and  $-1$. 
Only the values  $d(νT) = +1$  and  $d(νT) = -1$  are possible.

2

Which values are possible in PN modulation  (in the noise-free)  case?

$d(νT)$  can be Gaussian distributed.
$d(νT)$  can take the values  $+1$,  $0$  and  $-1$. 
Only the values  $d(νT) = +1$  and  $d(νT) = -1$  are possible.

3

What modification must be made to the BPSK model to make it applicable to PN modulation?

The noise  $n(t)$  must be replaced by  $n'(t) = n(t) · c(t)$. 
The integration must now be done over  $J · T$. 
The noise power  $σ_n^2$  must be reduced by a factor of  $J$. 

4

What is the bit error probability  $p_{\rm B}$  for  $10 \lg \ (E_{\rm B}/N_0) = 6\ \rm dB$  for PN modulation? 
Note:   For BPSK, the following applies in this case:   $p_{\rm B} ≈ 2.3 · 10^{–3}$.

The larger  $J$  is chosen, the smaller  $p_{\rm B}$ is.
The larger  $J$  is chosen, the larger  $p_{\rm B}$ is.
Independent of  $J$,  the value  $p_{\rm B} ≈ 2.3 · 10^{–3}$ is always obtained.


Solution

(1)  The  last solution  is correct:

  • We are dealing here with an optimal receiver.
  • Without noise,  the signal  $b(t)$  within each bit is constantly equal to  $+1$  or  $-1$.
  • From the given equation for the integrator
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
it follows that  $d(νT)$  can take only the values  $+1$  and  $-1$. 


(2)  Again the  last solution  is correct:

  • In the noise-free and interference-free case   ⇒   $n(t) = 0$,  the twofold multiplication by  $c(t) ∈ \{+1, –1\}$  can be omitted,
  • so that the upper model is identical to the lower model.


(3)  Solution 1  is correct:

  • Since both models are identical in the noise-free case,  only the noise signal has to be adjusted:   $n'(t) = n(t) · c(t)$.
  • In contrast,  the other two solutions are not applicable:
  • The integration must still be done over  $T = J · T_c$  and the PN modulation does not reduce the AWGN noise.


(4)  The  last solution  is correct:

  • Multiplying the AWGN noise by the high-frequency  $±1$ signal  $c(t)$,  the product is also Gaussian and white.
  • Because of  ${\rm E}\big[c^2(t)\big] = 1$,  the noise variance is not changed either.  Thus:
  • The equation  $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$  valid for BPSK is also applicable for PN modulation,  independent of spreading factor  $J$  and specific spreading sequence.
  • Ergo:  For AWGN noise,  band spreading neither increases nor decreases the error probability.