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Table 1.

Comparison between different related works and the proposed model.

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Table 1 Expand

Fig 1.

Proposed system model.

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Fig 1 Expand

Table 2.

Simulation parameters.

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Table 2 Expand

Fig 2.

Pearson correlation coefficients of each input parameter (dCB, , , SINRth, PI, PC, PD and PV) and the output (dIG, EE and R).

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Fig 2 Expand

Fig 3.

Proposed deep learning model.

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Fig 3 Expand

Fig 4.

Training and validation mean absolute error generated during training the proposed model.

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Fig 4 Expand

Fig 5.

Interference distance (m) vs required distance between IoT-sensors and gateway (dIG).

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Fig 5 Expand

Fig 6.

IoT-sensors transmission power (PI) (dBm) required distance between IoT-sensors and gateway (dIG) (m).

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Fig 6 Expand

Fig 7.

IoT-sensors transmission power (PI) (dBm) versus overall system energy efficiency (EE) (bit/J).

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Fig 7 Expand

Fig 8.

Required signal-to-interference-plus-noise-ratio (SINRth) versus required distance between IoT-sensors and gateway (dIG).

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Fig 8 Expand

Fig 9.

Required signal-to-interference-plus-noise-ratio (SINRth) versus overall system energy efficiency (EE) (bit/J).

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Fig 9 Expand

Fig 10.

Required signal-to-interference-plus-noise-ratio (SINRth) versus overall system achievable data rate (R) (bit/s).

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Fig 10 Expand

Fig 11.

IoT-sensors transmission power (PI) vs overall energy efficiency (EE).

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Fig 11 Expand