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Various scenarios and use cases are studied in this virtual RAN environment, network performance being evaluated for different situations, by varying guaranteed levels, serving weights, and used services.
We selected EVM, uncoded BER, and coded BER as figures of merit, all being evaluated for different SNR, CQI, and speed values.
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Additionally, the accuracy of the proposed approximate teletraffic model is evaluated for different evaluation scenarios.
Sentinel species, which readily accumulate pollutants and therefore serve as indicators of ecosystem health, have been evaluated for different environments, including terrestrial, freshwater, and marine habitats.
The results are evaluated for different system and fault conditions.
The kinetic parameters have been evaluated for different temperatures.
This effect is evaluated for different characteristic spotting distances.
The prediction performance is evaluated for different prediction intervals.
The REWL algorithm, with, was evaluated for different node densities, with the two different frequencies.
Thereby, for each algorithm, the performance is evaluated for different average number of users per sector.
Finally, the transmission performance of the proposed method is evaluated for different traffic scenarios.
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