JDAPCOO: Resource Scheduling and Energy Efficiency Optimization in 5G and Satellite Converged Networks for Power Transmission and Distribution Scenarios

. 2022 Sep 19;22(18):7085. doi: 10.3390/s22187085

Algorithm 2: Improved power control scheme based on simulated annealing algorithm

1:
Input: PD power maximum $P_{max}$ and the minimum transmission rate requirement of the PDs $R_{t h}$ .
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Output: Optimal power control scheme ${P (t)}$ .
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Initialize: Initial temperature $T_{0}$ , original cooling rate $V_{d e c r e a s e}$ , additional cooling rate $v_{d e c r e a s e}$ , termination temperature $T_{e n d}$ and the number of iterations $L_{i t e r a t i o n}$ .
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Randomly generate a random initial solution $p_{1}$ to the subproblem $SP 2$ .
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Calculate $f (p_{1})$ .
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repeat
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for temperature $T_{0}$ do
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Set $k = 0$ , $r = 0$ .
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repeat
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Randomly generate a random initial solution $p_{2}$ to the subproblem $SP 2$ .
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Calculate $f (p_{2})$ .
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Calculate $Δ f = f (p_{2}) - f (p_{1})$ .
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if $Δ f > 0$ then
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$p_{1} = p_{2}$ .
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$r = r + 1$ .
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else
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Generate a uniformly distributed random number ∂ in the interval [0,1].
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if $e^{\frac{Δ f}{T_{0}}} > \partial$ then
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$p_{1} = p_{2}$ .
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end if
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end if
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$k = k + 1$ .
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until $k > L_{i t e r a t i o n}$ .
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if $r > 0$ then
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$T_{0} = T_{0} \times v_{d e c r e a s e}$ .
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end if
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$T_{0} = T_{0} \times V_{d e c r e a s e}$ .
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end for
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until $T_{0} < T_{e n d}$ .
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Return $p_{1}$ .