Difference between revisions of "Aufgaben:Exercise 3.3Z: Optimization of a Coaxial Cable System"
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− | {{quiz-Header|Buchseite= | + | {{quiz-Header|Buchseite=Digital_Signal_Transmission/Consideration_of_Channel_Distortion_and_Equalization |
}} | }} | ||
− | [[File:P_ID1409__Dig_Z_3_3.png|right|frame| | + | [[File:P_ID1409__Dig_Z_3_3.png|right|frame|Normalized system parameters for different cutoff frequencies]] |
− | + | We consider a redundancy-free binary transmission system with the following specifications: | |
− | * | + | * The transmission pulses are NRZ rectangular and have energy EB=s20⋅T. |
− | * | + | |
− | * | + | * The channel is a coaxial cable with characteristic cable attenuation a∗=40dB. |
− | * | + | |
+ | * AWGN noise with (one-sided) noise power density N0=0.0001⋅EB is present. | ||
+ | |||
+ | * The receiver frequency response HE(f) includes an ideal channel equalizer H−1K(f) and a Gaussian low-pass filter HG(f) with cutoff frequency fG for noise power limitation. | ||
− | + | The table shows the eye opening ¨o(TD) as well as the detection noise rms value σd – each normalized to the transmitted amplitude s0 – for different cutoff frequencies fG. The cutoff frequency is to be chosen such that the worst-case error probability is as small as possible, with the following definition: | |
:$$p_{\rm U} = {\rm Q} \left( \frac{\ddot{o}(T_{\rm D})/2}{ \sigma_d} | :$$p_{\rm U} = {\rm Q} \left( \frac{\ddot{o}(T_{\rm D})/2}{ \sigma_d} | ||
\right) \hspace{0.3cm}\Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q} \left( \sqrt{\rho_{\rm U}}\right)$$ | \right) \hspace{0.3cm}\Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q} \left( \sqrt{\rho_{\rm U}}\right)$$ | ||
− | * | + | *This quantity represents an upper bound for the mean error probability pS≤pU. |
− | * | + | |
+ | *For f_{\rm G} \cdot T ≥ 0.4, a lower bound can also be given: pS≥pU/4. | ||
+ | Notes: | ||
+ | *The exercise belongs to the chapter [[Digital_Signal_Transmission/Consideration_of_Channel_Distortion_and_Equalization|"Consideration of Channel Distortion and Equalization"]]. | ||
− | + | * Use the interaction module [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen|"Complementary Gaussian Error Functions"]] for numerical evaluation of the Q-function. | |
− | |||
− | * | ||
− | |||
− | === | + | ===Questions=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {Within the given grid, determine the optimal cutoff frequency with respect to the "worst-case error probability" criterion. |
|type="{}"} | |type="{}"} | ||
fG, opt⋅T = { 0.4 3% } | fG, opt⋅T = { 0.4 3% } | ||
− | { | + | {What values does this give for the "worst-case signal-to-noise ratio" and the worst-case error probability? |
|type="{}"} | |type="{}"} | ||
fG=G, opt:10⋅lgρU = { 5.41 3% } dB | fG=G, opt:10⋅lgρU = { 5.41 3% } dB | ||
pU = { 3.1 3% } % | pU = { 3.1 3% } % | ||
− | { | + | {To what value would we need to reduce the noise power density N0 (with respect to signal energy) so that pU is not greater than 10−6? |
|type="{}"} | |type="{}"} | ||
N0/EB = { 1.53 3% } ⋅10−5 | N0/EB = { 1.53 3% } ⋅10−5 | ||
− | { | + | {For the assumptions made in '''(3)''', give a lower and an upper bound for the "average error probability" pS. |
|type="{}"} | |type="{}"} | ||
p S, min = { 0.25 3% } ⋅10−6 | p S, min = { 0.25 3% } ⋅10−6 | ||
Line 50: | Line 53: | ||
</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(1)''' | + | '''(1)''' For the optimization it is sufficient to maximize the quotient ¨o(TD)/σd: |
− | * | + | *This is maximized from the values given in the table for the cutoff frequency fG,opt⋅T=0.4_ with 0.735/0.197≈3.73. |
− | * | + | *As a comparison: For fG⋅T=0.3 the result is 0.192/0.094≈2.04 due to the smaller eye opening. |
− | * | + | *For fG⋅T=0.5 the quotient is also smaller than for the optimum: 1.159/0.379≈3.05. |
+ | *An even larger cutoff frequency leads to a very large noise rms value without simultaneously increasing the vertical eye opening in the same way. | ||
− | '''(2)''' | + | '''(2)''' Using the result from '''(1)''', we further obtain: |
:$$\rho_{\rm U} = \left ( {3.73}/{2} \right )^2 \approx 3.48 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} | :$$\rho_{\rm U} = \left ( {3.73}/{2} \right )^2 \approx 3.48 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} | ||
10 \cdot {\rm | 10 \cdot {\rm | ||
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− | '''(3)''' | + | '''(3)''' With the given 10⋅lgEB/N0=40 dB, i.e. EB/N0=104, the worst-case signal-to-noise ratio has been found to be 10⋅lgρU≈5.41dB. |
− | + | *However, for the worst-case error probability pU=10−6 ⇒ 10⋅lgρU>13.55dB must be obtained. | |
− | * | + | *This is achieved by increasing the quotient EB/N0 accordingly: |
− | * | ||
:$$10 \cdot {\rm | :$$10 \cdot {\rm | ||
lg}\hspace{0.1cm}{E_{\rm B}}/{N_0} = 40\,{\rm dB} | lg}\hspace{0.1cm}{E_{\rm B}}/{N_0} = 40\,{\rm dB} | ||
Line 81: | Line 84: | ||
'''(4)''' | '''(4)''' | ||
− | * | + | *The upper bound for pS is equal to the worst-case error probability pU=10−6_. |
− | * | + | |
+ | *The lower bound is 0.25⋅10−6_, which is smaller by a factor of $4$. | ||
{{ML-Fuß}} | {{ML-Fuß}} | ||
− | [[Category:Digital Signal Transmission: Exercises|^3.3 | + | [[Category:Digital Signal Transmission: Exercises|^3.3 Channel Distortion and Equalization^]] |
Latest revision as of 15:06, 28 June 2022
We consider a redundancy-free binary transmission system with the following specifications:
- The transmission pulses are NRZ rectangular and have energy EB=s20⋅T.
- The channel is a coaxial cable with characteristic cable attenuation a∗=40dB.
- AWGN noise with (one-sided) noise power density N0=0.0001⋅EB is present.
- The receiver frequency response HE(f) includes an ideal channel equalizer H−1K(f) and a Gaussian low-pass filter HG(f) with cutoff frequency fG for noise power limitation.
The table shows the eye opening ¨o(TD) as well as the detection noise rms value σd – each normalized to the transmitted amplitude s0 – for different cutoff frequencies fG. The cutoff frequency is to be chosen such that the worst-case error probability is as small as possible, with the following definition:
- pU=Q(¨o(TD)/2σd)⇒pU=Q(√ρU)
- This quantity represents an upper bound for the mean error probability pS≤pU.
- For fG⋅T≥0.4, a lower bound can also be given: pS≥pU/4.
Notes:
- The exercise belongs to the chapter "Consideration of Channel Distortion and Equalization".
- Use the interaction module "Complementary Gaussian Error Functions" for numerical evaluation of the Q-function.
Questions
Solution
(1) For the optimization it is sufficient to maximize the quotient ¨o(TD)/σd:
- This is maximized from the values given in the table for the cutoff frequency fG,opt⋅T=0.4_ with 0.735/0.197≈3.73.
- As a comparison: For fG⋅T=0.3 the result is 0.192/0.094≈2.04 due to the smaller eye opening.
- For fG⋅T=0.5 the quotient is also smaller than for the optimum: 1.159/0.379≈3.05.
- An even larger cutoff frequency leads to a very large noise rms value without simultaneously increasing the vertical eye opening in the same way.
(2) Using the result from (1), we further obtain:
- ρU=(3.73/2)2≈3.48⇒10⋅lgρU=5.41dB_⇒pU=Q(3.73/2)≈0.031_.
(3) With the given 10⋅lgEB/N0=40 dB, i.e. EB/N0=104, the worst-case signal-to-noise ratio has been found to be 10⋅lgρU≈5.41dB.
- However, for the worst-case error probability pU=10−6 ⇒ 10⋅lgρU>13.55dB must be obtained.
- This is achieved by increasing the quotient EB/N0 accordingly:
- 10⋅lgEB/N0=40dB+13.55dB−5.41dB=48.14dB⇒EB/N0=104.814≈65163⇒N0/EB=1.53⋅10−5_.
(4)
- The upper bound for pS is equal to the worst-case error probability pU=10−6_.
- The lower bound is 0.25⋅10−6_, which is smaller by a factor of 4.