Power control method for cooperating with Internet of things energy acquisition node
An energy harvesting and power control technology, applied in the field of Internet of Things, which can solve the problem of not fully considering the optimal energy saving scheme of network throughput and so on
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Embodiment 1
[0104] A power control method based on collaborative Internet of Things energy harvesting nodes, comprising:
[0105] Step 1: System scene analysis, problem analysis:
[0106] Considering a three-node scenario with energy harvesting based on the collaborative Internet of Things, the present invention is aimed at a special application scenario, sourced from practical applications, and the scenario setting is detailed and reasonable, and has more practical guiding significance. In the scenario, there is an energy harvesting end user A, an energy harvesting relay station R, and a target communication end user B. Considering the existence of a direct path between the energy harvesting end user A and the target communication end user B, the energy harvesting relay station R Select the decoding and forwarding (DecodeForward, abbreviated as DF) working mode. The present invention considers the use of idle nodes in the network as relay stations to participate in cooperative forwardin...
Embodiment 2
[0174] On the basis of Embodiment 1 of the present invention, we make further improvements and select more precise power control to improve the accuracy of the algorithm. Specifically, the step 3 includes:
[0175] Solve the subproblem P2 as follows:
[0176] Step A: set i=1, when i≤N, repeat until the algorithm ends;
[0177] Step B: Calculate i separately a and as follows:
[0178] i a = arg min i ≤ j ≤ N { Σ k = i j E S ( k ) ( j - i + 1 ) B ...
Embodiment 3
[0184] On the basis of the second embodiment of the present invention, we further improve it by adopting a convex optimization method to perform convex optimization processing on the sub-problem P3 to obtain a new equivalent optimization problem P4, and the solution complexity is significantly reduced. Specifically, the step 4 includes:
[0185] Convex optimization is performed on the sub-problem P3 to obtain a new equivalent optimization problem P4, and the complexity of the solution is significantly reduced.
[0186] P 4 : m a x r ( i + 1 ) ≥ 0 ...
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