节点文献

Power control and channel allocation optimization game algorithm with low energy consumption for wireless sensor network

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 郝晓辰刘金硕解力霞陈白姚宁

【Author】 Xiao-Chen Hao;Jin-Shuo Liu;Li-Xia Xie;Bai Chen;Ning Yao;School of Electrical Engineering, Yanshan University;

【通讯作者】 郝晓辰;

【机构】 School of Electrical Engineering, Yanshan University

【摘要】 In a wireless sensor network(WSN), the energy of nodes is limited and cannot be charged. Hence, it is necessary to reduce energy consumption. Both the transmission power of nodes and the interference among nodes influence energy consumption. In this paper, we design a power control and channel allocation game model with low energy consumption(PCCAGM). This model contains transmission power, node interference, and residual energy. Besides, the interaction between power and channel is considered. The Nash equilibrium has been proved to exist. Based on this model, a power control and channel allocation optimization algorithm with low energy consumption(PCCAA) is proposed. Theoretical analysis shows that PCCAA can converge to the Pareto Optimal. Simulation results demonstrate that this algorithm can reduce transmission power and interference effectively. Therefore, this algorithm can reduce energy consumption and prolong the network lifetime.

【Abstract】 In a wireless sensor network(WSN), the energy of nodes is limited and cannot be charged. Hence, it is necessary to reduce energy consumption. Both the transmission power of nodes and the interference among nodes influence energy consumption. In this paper, we design a power control and channel allocation game model with low energy consumption(PCCAGM). This model contains transmission power, node interference, and residual energy. Besides, the interaction between power and channel is considered. The Nash equilibrium has been proved to exist. Based on this model, a power control and channel allocation optimization algorithm with low energy consumption(PCCAA) is proposed. Theoretical analysis shows that PCCAA can converge to the Pareto Optimal. Simulation results demonstrate that this algorithm can reduce transmission power and interference effectively. Therefore, this algorithm can reduce energy consumption and prolong the network lifetime.

【基金】 Project supported by the National Natural Science Foundation of China(Grant No.61403336);the Natural Science Foundation of Hebei Province,China(Grant Nos.F2015203342 and F2015203291);the Independent Research Project Topics B Category for Young Teacher of Yanshan University,China(Grant No.15LGB007)
  • 【文献出处】 Chinese Physics B ,中国物理B , 编辑部邮箱 ,2018年08期
  • 【分类号】O225;TN929.5;TP212.9
  • 【被引频次】1
  • 【下载频次】64
节点文献中: