蜂窝网络中延迟最小化用户关联的原始对偶方法

J. Wildman, Yusuf Osmanlioglu, S. Weber, A. Shokoufandeh
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引用次数: 4

摘要

我们在蜂窝单用户关联(SUA)策略的背景下研究网络效用最大化(NUM),该策略将每个移动用户(MU)映射到单个基站(BS),并利用跨下行速率的广义α-比例公平效用度量。众所周知,找到许多这样的集中式用户关联问题的精确解是np困难的,因此我们有动机考虑SUA NUM问题的整数松弛。在这方面,我们提供了i)在SUA NUM问题完整性缺口恰好为1的公平性度量,以及ii)产生非凸SUA NUM问题公式的公平性度量的单独表征。接下来,我们分析了与延迟最小化相对应的公平性度量,并找到了一种比我们之前的相关工作更自然的非凸最小延迟SUA问题的线性化。我们提出并构造了一种近似线性化最小延迟SUA问题的原对偶算法。我们的原始对对算法被证明可以实现更小的性能差距和运行时间,i)应用于线性化最小延迟SUA问题的直观基线舍入算法,以及ii)两个贪心启发式算法,分别强调最小MU-BS距离和最大下行SINR比的关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A primal-dual approach to delay minimizing user association in cellular networks
We study network utility maximization (NUM) within the context of cellular single user association (SUA) policies that map each mobile user (MU) to a single base station (BS) and make use of the generalized α-proportional fairness utility measure across downlink rates. Finding an exact solution to many such centralized user association problem is known to be NP-hard, so we are motivated to consider the integer relaxation of the SUA NUM problem. On this front, we provide separate characterizations of i) the fairness measures under which the SUA NUM problem integrality gap is exactly 1, and ii) the fairness measures yielding non-convex SUA NUM problem formulations. Next, we analyze the fairness measure corresponding to delay minimization and find a more natural linearization of the non-convex minimum delay SUA problem compared to our related previous work. We propose and construct a primal-dual algorithm to approximate the linearized minimum delay SUA problem. Our primal-dual algorithm is shown to achieve smaller performance gaps and runtimes over i) an intuitive baseline rounding algorithm applied to the linearized min delay SUA problem, as well as ii) two greedy heuristics that emphasize associations with minimal MU-BS distances and maximal downlink SINR ratios, respectively.
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