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Interference Networks with Local View: A Distributed Optimization Approach

机译:具有局部视图的干扰网络:一种分布式优化方法

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In practice, a node in a network learns the channel through local message passing and obtains a local view of the network. Pure wireless message passing as well as mixed wireless and wireline message passing are considered in this paper. We study the distributed optimization of sum-rate for a class of deterministic interference networks with local view. A connection based utility function is designed for each user to exploit the local knowledge. This utility design turns out to be a potential game with sum-rate as the potential function. For the one-to-many channel with 1.5 wireless rounds of message passing, we show that there is a unique Nash equilibrium and using this strategy, the sum capacity can be achieved. We provide a sufficient condition for which a topology does not have unique Nash equilibrium. Then we consider the scenario that the network size and the users IDs are provided to each user. For various mixed wireless and wireline message passing patterns, including wireline at transmitter/receiver side and sequential/concurrent message passing scheduling, we identify whether a three-user interference network can achieve the sum capacity in a distributed fashion. Compared with the 1.5 pure wireless rounds of message passing, the results show that 2.5 mixed wireless and wireline rounds of message passing can significantly improve the system performance of three-user interference networks. We also derive some sufficient conditions for general K-user interference networks such that the sum capacity can not be achieved based on each user's local view.
机译:实际上,网络中的节点通过本地消息传递来学习信道并获得网络的本地视图。本文考虑了纯无线消息传递以及无线和有线混合消息传递。我们研究了一类具有局部视图的确定性干扰网络的总速率分布式优化。为每个用户设计了基于连接的实用程序功能,以利用本地知识。该实用程序设计证明是一个以总和为潜在函数的潜在游戏。对于具有1.5个无线轮次消息传递的一对多通道,我们表明存在唯一的纳什均衡,并且使用此策略,可以实现总容量。我们提供了一个拓扑不具有唯一Nash平衡的充分条件。然后,我们考虑为每个用户提供网络大小和用户ID的情况。对于各种混合的无线和有线消息传递模式,包括发送器/接收器端的有线和顺序/并发消息传递调度,我们确定三用户干扰网络是否可以以分布式方式实现总容量。与1.5次纯无线消息传递相比,结果显示2.5次无线和有线混合消息传递可以显着提高三用户干扰网络的系统性能。我们还为一般的K用户干扰网络得出了一些充分的条件,使得无法基于每个用户的本地视图获得总容量。

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