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Energy-efficient user association in cellular networks: A population game approach

机译:蜂窝网络中的高能效用户关联:总体博弈方法

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In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).
机译:在本文中,我们以节能的方式解决了将移动台与基站(BS)关联的问题。我们采用人口博弈的方法,该方法可以对许多自私的手机进行简单的分析,而不会增加数学的复杂性,其中我们的研究对节能的BS关联提供了两个实际含义:(i)如何控制所谓的关联定价,以便整个蜂窝网络的运行旨在优化社会目标,以及(ii)如何开发分布式的,节能的关联算法。为此,我们首先定义一个游戏,其中移动台是玩家,他们与不同基站的关联部分是他们的策略。然后,从我们的均衡分析中,我们证明了运营商进行的简单的基于功率的定价会导致Nash均衡等于社会优化问题的最优解(即零无政府定价)。接下来,我们研究移动台的三个演化动力学,每个动力学方程都表示为一个微分方程,并将它们分别连接到分布式关联控制机制,其中三个动力学可证明地或通过实验收敛到纳什均衡(等于社会最优点) )。

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