无线网络效用最大化算法的收敛性分析

Convergence Analysis of Wireless Network Utility Maximization Algorithm

  • 摘要: 针对分布式效用最大化算法中的信息交互和反馈易于受随机噪声干扰,研究了随机噪声对分布式效用最大化算法收敛性影响问题. 通过将随机噪声模拟为鞅,采用鞅方法分析了随机噪声对分布式效用最大化算法的影响,给出并证明了带有反馈噪声的分布式效用最大化算法几乎处处收敛的一个充分条件. 仿真实验验证了理论分析的正确性.

     

    Abstract: Due to the information interaction and feedback signals can be easily affected by stochastic noise, in this paper, the impact of stochastic noise on the convergence of the distributed network utility maximization algorithms was studied. The impact of stochastic noise on the distributed NUM algorithms was presented, and a sufficient condition under which the distributed NUM algorithms almost everywhere converge was provided and proved by modeling the stochastic noise as martingale and using martingale analysis method. Simulation experiments validate the conclusion of our theoretical analyses.

     

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