Table 1.
Research gap in existing approaches and DALFM’s contributions.
Fig 1.
System model.
Fig 2.
Amplification loss function with and without sampling loss.
Fig 3.
(a) High and (b) low analysis of sampling rate.
Fig 4.
RL process for sampling rate fixation.
Fig 5.
Process of recurrent learning.
Fig 6.
Amplification loss function rate analysis for weights assigned.
Fig 7.
estimated and observed (a) amplification loss function and (b) time interval.
Fig 8.
Transmission gain for (a) amplification loss function and (b) sampling rate.
Table 2.
Parameter settings.
Fig 9.
Performance assessment of transmission gain (a) received power and (b) intervals.
Fig 10.
Performance assessment of path loss for (a) received power, (b) intervals.
Fig 11.
Sampling rate comparative illustration between existing methods and proposed module; (a) received power, (b) intervals.
Fig 12.
Error rate analysis for (a) received power and (b) intervals.
Fig 13.
Communication rate assessment (a) received power (b) intervals.
Table 3.
Comparison of DALFM with existing methods in dynamic 5G air-to-terrestrial network.