Multiuser rate allocation games for multimedia communications
Multiuser rate allocation games for multimedia communications
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DOI：
10.1109/tmm.2009.2026101
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发表时间：
2009-10
影响因子：
7.3
通讯作者：
Yan Chen;Beibei Wang;K. Liu
中科院分区：
文献类型：
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作者：
Yan Chen;Beibei Wang;K. Liu
在多用户多媒体通信中，如何在不同用户之间有效、公平地分配数据速率是一个关键问题。然而，大多数现有的基于优化的方法，如最小化失真的加权和或最大化峰值信噪比（PSNR）的加权和，有他们的权重明确地确定。此外，这些方法主要侧重于效率问题，而没有公平的概念。在本文中，我们解决这个问题，提出了一个博弈论的框架，其中每个用户/播放器的效用/收益函数共同确定的传输的视频序列和分配的比特率的特性。我们表明，一个独特的纳什均衡（NE），这是按比例公平的效用和PSNR，可以得到，根据控制器可以有效地和公平地分配可用的网络带宽给用户。此外，我们提出了一个分布式的防作弊的速率分配方案的用户收敛到最佳NE使用替代上升时钟拍卖。我们还表明，传统的基于优化的方法，最大限度地提高加权和的PSNR是一个特殊的情况下的博弈论框架的效用函数定义为指数函数的PSNR。最后，我们给出了几个实验结果对真实的视频数据证明所提出的方法的效率和有效性。
How to efficiently and fairly allocate data rate among different users is a key problem in the field of multiuser multimedia communication. However, most of the existing optimization-based methods, such as minimizing the weighted sum of the distortions or maximizing the weighted sum of the peak signal-to-noise ratios (PSNRs), have their weights heuristically determined. Moreover, those approaches mainly focus on the efficiency issue while there is no notion of fairness. In this paper, we address this problem by proposing a game-theoretic framework, in which the utility/payoff function of each user/player is jointly determined by the characteristics of the transmitted video sequence and the allocated bit-rate. We show that a unique Nash equilibrium (NE), which is proportionally fair in terms of both utility and PSNR, can be obtained, according to which the controller can efficiently and fairly allocate the available network bandwidth to the users. Moreover, we propose a distributed cheat-proof rate allocation scheme for the users to converge to the optimal NE using alternative ascending clock auction. We also show that the traditional optimization-based approach that maximizes the weighted sum of the PSNRs is a special case of the game-theoretic framework with the utility function defined as an exponential function of PSNR. Finally, we show several experimental results on real video data to demonstrate the efficiency and effectiveness of the proposed method.