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(i) Scenario 1.
We examine the following scenarios: (i) scenario 1: dB, (ii) scenario 2: dB and dB, (iii) scenario 3: dB, (iv) scenario 4: dB and dB. .
Based on the illustration scenario in Figure 1, we study the following scenarios: (i) Scenario 1 is a comparison of the analytical results in a high density area (i.e., 80% traffic load).
The scenarios analyzed are the following: (i) Scenario #1: Standard OLSR, (ii) Scenario #2: HOP using 2 pseudonyms per node, (iii) Scenario #3: HOP using 3 pseudonyms per node. .
The effect of the uncoordinated power is examined by considering the following scenarios where dBm: (i) scenario 5: dBm, (ii) (ii)scenario 6: dBm and dBm, (iii) scenario 7: dBm and dBm, (iv) scenario 8: dBm and dBm. .
The two channel estimation algorithms proposed in the paper, namely, the LS and the MST, have been evaluated in two different scenarios: (i) Scenario A: the two links have the same SNR.
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For DFE-I scenario the BER performance significantly improves by increasing up to, for which the performance is rather steady.
This complexity is the same complexity associated with computing the feed-forward filter coefficients of DFE-I scenario and the linear equalizer.
Strategy I (for Scenario I) is designed when only the training dataset is selectable.
Rapidly increased bandwidth of vehicle communication brings challenges on its infrastructure, especially for V2R/V2I scenarios.
In order to test the aforementioned approaches, three different scenarios of the evaluation were proposed: i. Scenario 1. Murmur detection of PCG signals.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com