如何(信息理论上)最优的分布式决策?

V. Aggarwal, A. Avestimehr, A. Sabharwal
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引用次数: 4

摘要

“如果我们知道得更多,我们就能取得更多成就。”这句谚语也适用于网络,其中关于网络状态的更多信息转化为更高的求和速率。在本文中,我们形式化了随着网络知识的增加而增加的求和速率。网络的知识是根据网络信息的跳数来衡量的,而和率是通过信息完整时所能达到的最大和率来规范化的。随着网络知识的增加,可实现的归一化和速率也增加。最好的归一化和速率称为归一化和容量。本文在瞬时信道信息为一跳和二跳的情况下,刻画了多类确定性干扰网络的归一化和容量随网络信息跳数的增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How (information theoretically) optimal are distributed decisions?
“If we know more, we can achieve more.” This adage also applies to networks, where more information about the network state translates into higher sum-rates. In this paper, we formalize this increase of sum-rate with increased knowledge of network. The knowledge of network is measured in terms of the number of hops of information about the network while the sum-rate is normalized by the maximum sum-rate that can be achieved with complete information. As the knowledge about the network increase, the achievable normalized sum-rate also increases. The best normalized sum-rate is called normalized sum-capacity. In this paper, we characterize the increase of normalized sum-capacity with the hops of information about the network for many classes of deterministic interference networks for the cases of one and two-hops of instantaneous channel information.
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