A Game Theoretic Framework for Power Control in Wireless Sensor Networks
A Game Theoretic Framework for Power Control in Wireless Sensor Networks
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DOI：
10.1109/tc.2009.82
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发表时间：
2010-02-01
影响因子：
3.7
通讯作者：
Kwiat, Kevin A.
中科院分区：
文献类型：
--
作者：
Sengupta, Shamik;Chatterjee, Mainak;Kwiat, Kevin A.
在无基础设施的传感器网络中，由于传感器节点可用的能量有限，因此有效地使用能量是非常关键的。在消耗能量的各种现象中，无线电通信是迄今为止要求最高的一种。限制不必要的能量损失的有效方法之一是控制节点发送信号的功率。在本文中，我们应用博弈论来解决基于CDMA的分布式传感器网络的功率控制问题。我们建立了一个不完全信息下的非合作博弈模型，并研究了纳什均衡的存在性。借助这种平衡，我们设计了一个分布式算法的最优功率控制，并证明了系统是功率稳定的，只有当节点符合一定的发射功率阈值。我们表明，即使在一个非合作的情况下，它是符合这些阈值的节点的最佳利益。评估节点应该传输的功率电平，以最大化其效用。此外，我们比较了效用时，节点被允许发送与离散和连续的功率水平，与离散水平的性能是上界的连续情况。我们定义了一个失真度量，它给出了一个定量的衡量有有限的功率水平的好处，也找到那些水平，最大限度地减少失真。数值结果表明，该算法实现了最好的收益/效用的传感器节点，即使消耗更少的功率。
In infrastructure-less sensor networks, efficient usage of energy is very critical because of the limited energy available to the sensor nodes. Among various phenomena that consume energy, radio communication is by far the most demanding one. One of the effective ways to limit unnecessary energy loss is to control the power at which the nodes transmit signals. In this paper, we apply game theory to solve the power control problem in a CDMA-based distributed sensor network. We formulate a noncooperative game under incomplete information and study the existence of Nash equilibrium. With the help of this equilibrium, we devise a distributed algorithm for optimal power control and prove that the system is power stable only if the nodes comply with certain transmit power thresholds. We show that even in a noncooperative scenario, it is in the best interest of the nodes to comply with these thresholds. The power level at which a node should transmit, to maximize its utility, is evaluated. Moreover, we compare the utilities when the nodes are allowed to transmit with discrete and continuous power levels; the performance with discrete levels is upper bounded by the continuous case. We define a distortion metric that gives a quantitative measure of the goodness of having finite power levels and also find those levels that minimize the distortion. Numerical results demonstrate that the proposed algorithm achieves the best possible payoff/utility for the sensor nodes even by consuming less power.