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task 5 done

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ti_mo
2026-06-12 16:09:25 +02:00
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lab_4/link_level_measurements.md
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@@ -193,4 +193,26 @@ So in this simulation a higher bandwith improves PER.
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## Task 5
## Task 5
#### 5.1
![PER over SNR Channel Profile sweep](per_snr_profile.svg)
For readability, the labels NTN-TDL-A to NTN-TDL-D are shortened to Profile A to Profile D in the plot.
The channel profile sweep shows that the selected NTN-TDL profile has a visible influence on the PER curve. Profile C performs best in this simulation, while Profile B requires the highest SNR for the same target PER. Around the low-PER region, Profile C reaches a PER of approximately $10^{-3}$ about 5 dB earlier than Profile B. Profiles D and A lie between these two cases, with roughly 1-3 dB spacing between neighboring curves for PER values below $10^{-1}$.
This means that the channel profile changes the effective link robustness even though all other baseline parameters are kept constant. The difference is caused by the different multipath and fading behavior represented by the NTN-TDL profiles.
#### 5.2
![CFR Comparision on SNR 30 between NTN-TDL Channel Profiles](cfr_comp.svg)
The CFR comparison shows that the NTN-TDL profiles create different frequency-selective channel responses. Profile C has the flattest and highest CFR magnitude at around 1.4 to 1.6 over the active subcarriers, which means that the subcarriers experience a relatively uniform channel gain without strong frequency-selective fades. This is consistent with the PER sweep from Task 5.1, where Profile C performs best.
Profiles A and B show stronger variations and deeper periodic fades over the subcarrier range. These fades reduce the effective SNR on parts of the OFDM spectrum and can therefore increase the packet error probability. Profile D lies between these cases, with visible but more moderate frequency-selective behavior.
Since this plot shows only one representative packet at 30 dB SNR and 320 MHz bandwidth, it should be interpreted qualitatively. It illustrates how the different channel profiles affect the frequency response, while the PER sweep provides the statistical performance comparison.
[This tasks (5.2) interpretation was mainly made from GPT-5.5, because I was not sure what I should assume from the data, after evaluating what GPT interpeted, it made sense and I can see / evaluate the meaning behind the plot]