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首页> 外文期刊>IEEE/ACM Transactions on Networking >To Transmit or Not to Transmit? Distributed Queueing Games in Infrastructureless Wireless Networks
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To Transmit or Not to Transmit? Distributed Queueing Games in Infrastructureless Wireless Networks

机译:传输还是不传输?无基础架构无线网络中的分布式排队游戏

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摘要

We study distributed queueing games in interference-limited wireless networks. We formulate the throughput maximization problem via distributed selection of users' transmission thresholds as a Nash Equilibrium Problem (NEP). We first focus on the solution analysis of the NEP and derive sufficient conditions for the existence and uniqueness of a Nash Equilibrium (NE). Then, we develop a general best-response-based algorithmic framework wherein the users can explicitly choose the degree of desired cooperation and signaling, converging to different types of solutions, namely: 1) a NE of the NEP when there is no cooperation among users and 2) a stationary point of the Network Utility Maximization (NUM) problem associated with the NEP, when some cooperation among the users in the form of (pricing) message passing is allowed. Finally, as a benchmark, we design a globally optimal but centralized solution method for the nonconvex NUM problem. Our experiments show that in many scenarios the sum-throughput at the NE of the NEP is very close to the global optimum of the NUM problem, which validates our noncooperative and distributed approach. When the gap of the NE from the global optimality is non negligible (e.g., in the presence of “high” coupling among users), exploiting cooperation among the users in the form of pricing enhances the system performance.
机译:我们研究了受干扰限制的无线网络中的分布式排队游戏。我们通过分布式选择用户的传输阈值将吞吐量最大化问题表述为纳什均衡问题(NEP)。我们首先关注NEP的解决方案分析,并得出满足纳什均衡(NE)的存在和唯一性的充分条件。然后,我们开发了一个基于最佳响应的通用算法框架,在该框架中,用户可以明确选择所需的协作和信令程度,从而收敛到不同类型的解决方案,即:1)当用户之间没有协作时,NEP的NE 2)当允许用户之间以(定价)消息传递的形式进行一些合作时,与NEP相关的网络效用最大化(NUM)问题的固定点。最后,作为基准,我们针对非凸NUM问题设计了一种全局最优但集中式的求解方法。我们的实验表明,在许多情况下,NEP的NE处的总吞吐量非常接近NUM问题的全局最优值,这证明了我们的非合作和分布式方法。当NE与全局最优性之间的差距不可忽略时(例如,在用户之间存在“高”耦合)时,以定价形式利用用户之间的合作可提高系统性能。

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