Aufgaben:Exercise 5.2Z: About PN Modulation: Difference between revisions
From LNTwww
No edit summary |
Fix interlanguage link: resolve redirect chain |
||
| (26 intermediate revisions by 6 users not shown) | |||
| Line 1: | Line 1: | ||
{{quiz-Header|Buchseite= | {{quiz-Header|Buchseite=Modulation_Methods/Direct-Sequence_Spread_Spectrum_Modulation | ||
}} | }} | ||
[[File: | [[File:EN_Bei_A_4_5.png|right|frame|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: | |||
*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. | |||
===Questions=== | |||
<quiz display=simple> | <quiz display=simple> | ||
{ | {Which detection signal values are possible with BPSK (in the noise-free case)? | ||
|type="[]"} | |type="[]"} | ||
- | - $d(νT)$ 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. | |||
{Which values are possible in PN modulation (in the noise-free) case? | |||
|type="[]"} | |||
- $d(νT)$ 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. | |||
{ | {What modification must be made to the BPSK model to make it applicable to PN modulation? | ||
|type="{} | |type="[]"} | ||
$\ | + 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 $J$. | |||
{What is the bit error probability $p_{\rm B}$ for $10 \lg \ (E_{\rm B}/N_0) = 6\ \rm dB$ for PN modulation? <br>Note: For BPSK, the following applies in this case: $p_{\rm B} ≈ 2.3 · 10^{–3}$. | |||
|type="()"} | |||
- 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. | |||
</quiz> | |||
===Solution=== | |||
{{ML-Kopf}} | |||
'''(1)''' The <u>last solution</u> 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 <u>last solution</u> 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)''' <u>Solution 1</u> 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 <u>last solution</u> 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. | |||
{{ML-Fuß}} | {{ML-Fuß}} | ||
[[Category: | [[Category:Modulation Methods: Exercises|^5.2 PN Modulation^]] | ||
[[de:Aufgaben:Aufgabe 5.2Z: Zur PN–Modulation]] | |||
Latest revision as of 17:54, 16 March 2026

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:
- This exercise belongs to the chapter 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.
Questions
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.