LTE中机会主义和公平资源分配调度的比较

Marco Centenaro, M. Pesce, D. Munaretto, A. Zanella, M. Zorzi
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引用次数: 5

摘要

高性能移动设备对数据流量的需求不断增加,以及通信基础设施升级带来的收益和成本之间的权衡,强烈推动网络运营商充分利用可用的网络资源,这更新并加强了对资源管理策略的兴趣。在这方面,一个关键的挑战在于在机会主义方法和基于公平的方法之间找到适当的平衡,机会主义方法旨在最大限度地提高携带流量的总量,而公平方法旨在在用户之间提供某种类型的公平。本文从总容量、用户公平性和调度程序复杂性等方面比较了LTE网络下行信道的几种资源分配策略。有两种方案基于匈牙利方法,该方法旨在将一个资源精确地关联到每个用户,同时最小化分配的总成本。因此,就分配的资源数量而言,这种方法在资源利用和用户公平性之间提供了一个很好的权衡。然后,我们提出了匈牙利方法的实际实现,即使在用户数量与可用资源数量不同,并且用户具有异构信道条件和提供的流量时也能工作。此外,我们考虑了第三种调度程序,它遵循背压方法,以机会主义的方式将资源分配给具有较长积压的用户,从而追求总吞吐量最大化和具有相同流量需求的用户之间的公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comparison between opportunistic and fair resource allocation scheduling for LTE
The increasing demand for data traffic through high capability mobile devices and the trade-off between revenues and costs for upgrading the communication infrastructures strongly push the network operators to make the best use of the available network resources, which renews and reinforces the interest on resource management strategies. In this respect, a key challenge consists in finding a proper balance between an opportunistic approach, which aims at maximizing the total amount of carried traffic, and a fairness-based approach that, instead, aims at providing some type of fairness among the users. In this paper, we compare a few resource allocation policies for the downlink channel of LTE networks in terms of aggregate capacity, user fairness, and scheduler complexity. Two schemes are based on the Hungarian method, which was designed to associate exactly one resource to each user, while minimizing the overall cost of the assignment. This method hence provides a nice tradeoff between resource exploitation and user fairness in terms of number of allocated resources. We then propose practical implementations of the Hungarian method that work even when the number of users differs from the number of available resources, and users have heterogenous channel conditions and offered traffic. In addition, we consider a third scheduler that follows a back-pressure approach, which which assignes resources to users with longer backlog in an opportunistic manner, thus pursuing both aggregate throughput maximization and fairness among users with equal traffic demand.
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