User Association in HetNets: Impact of Traffic Differentiation and Backhaul Limitations
User Association in HetNets: Impact of Traffic Differentiation and Backhaul Limitations
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HetNet 中的用户关联：流量差异化和回程限制的影响
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
U. Salim
中科院分区：
文献类型：
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作者：
Nikolaos Sapountzis;T. Spyropoulos;N. Nikaein;U. Salim
运营商正在努力不断增加容量并升级架构以跟上数据流量的增长，他们正在将注意力转向可提高频谱效率的更密集部署。更密集的部署使用户关联问题变得更具挑战性，并且人们投入了大量工作来寻找在用户服务质量和网络范围性能（负载平衡）之间进行权衡的算法。然而，这些算法中的大多数通常考虑使用单一类型流量的简单设置，通常是弹性非保证比特率 (GBR)。他们还关注无线接入部分，忽略回程拓扑和潜在的容量限制。回程约束正在成为未来网络的关键性能瓶颈，部分原因是无线电接口的不断改进，部分原因是需要廉价的回程链路以减少资本和运营支出。为此，我们提出了一种用户关联分析框架，共同考虑无线接入和回程网络性能。具体来说，我们推导了一种算法，该算法考虑了频谱效率、基站负载、回程链路容量和拓扑，以及上行链路和下行链路方向上的两种流量类别（GBR 和非 GBR）。我们通过分析证明了一种最佳用户关联规则，最终使不同维度（例如上行链路和下行链路性能或 GBR 和非 GBR 性能）所达到的性能的算术平均值或加权调和平均值最大化。然后，我们使用广泛的模拟来研究以下方面的影响：1）流量差异化； 2) 回程容量限制和关键性能指标的拓扑。
Operators, struggling to continuously add capacity and upgrade their architecture to keep up with data traffic increase, are turning their attention to denser deployments that improve spectral efficiency. Denser deployments make the problem of user association challenging, and much work has been devoted to finding algorithms that strike a tradeoff between user quality of service, and network-wide performance (load-balancing). Nevertheless, the majority of these algorithms typically consider simple setups with a single type of traffic, usually elastic non-guaranteed bit rate (GBR). They also focus on the radio access part, ignoring the backhaul topology and potential capacity limitations. Backhaul constraints are emerging as a key performance bottleneck in future networks, partly due to the continuous improvement of the radio interface, and partly due to the need for inexpensive backhaul links to reduce capital and operational expenditures. To this end, we propose an analytical framework for user association that jointly considers radio access and backhaul network performance. Specifically, we derive an algorithm that takes into account spectral efficiency, base station load, backhaul link capacities and topology, and two traffic classes (GBR and non-GBR) in both the uplink and downlink directions. We prove analytically an optimal user association rule that ends up maximizing either an arithmetic or a weighted harmonic mean of the achieved performance along different dimensions (e.g., uplink and downlink performances or GBR and non-GBR performances). We then use extensive simulations to study the impact of: 1) traffic differentiation; and 2) backhaul capacity limitations and topology on key performance metrics.