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首页> 外文期刊>Networking, IEEE/ACM Transactions on >Architecture and Abstractions for Environment and Traffic-Aware System-Level Coordination of Wireless Networks
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Architecture and Abstractions for Environment and Traffic-Aware System-Level Coordination of Wireless Networks

机译:无线网络的环境和流量感知系统级协调的体系结构和抽象

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This paper presents a system-level approach to interference management in an infrastructure-based wireless network with full frequency reuse. The key idea is to use loose base-station coordination that is tailored to the spatial load distribution and the propagation environment to exploit the diversity in a user population's sensitivity to interference. System architecture and abstractions to enable such coordination are developed for both the downlink and the uplink cases, which present differing interference characteristics. The basis for the approach is clustering and aggregation of traffic loads into classes of users with similar interference sensitivities that enable coarse-grained information exchange among base stations with greatly reduced communication overheads. This paper explores ways to model and optimize the system under dynamic traffic loads where users come and go, resulting in interference-induced performance coupling across base stations. Based on extensive system-level simulations, we demonstrate load-dependent reductions in file transfer delay ranging from 20%–80% as compared to a simple baseline not unlike systems used in the field today while simultaneously providing more uniform coverage. Average savings in user power consumption of up to 75% is achieved. Performance results under heterogeneous spatial loads illustrate the importance of being traffic- and environment-aware.
机译:本文提出了一种在具有全频率复用的基于基础架构的无线网络中进行干扰管理的系统级方法。关键思想是使用针对空间负载分布和传播环境量身定制的宽松基站协调,以利用用户群体对干扰的敏感性的多样性。针对下行链路和上行链路情况都开发了实现这种协调的系统架构和抽象,它们表现出不同的干扰特性。该方法的基础是将业务负载聚类和聚合到具有类似干扰敏感度的用户类别中,从而可以在基站之间以较粗略的信息交换进行粗粒度的信息交换,并大大降低了通信开销。本文探讨了在用户来来往往的动态流量负载下对系统进行建模和优化的方法,这些方法导致了基站之间干扰引起的性能耦合。基于广泛的系统级仿真,我们证明了与简单基准相比,文件传输延迟在20%–80%范围内与负载相关的减少,与今天的现场系统不同,同时提供了更统一的覆盖范围。可以平均节省多达75%的用户功耗。异构空间负载下的性能结果说明了了解流量和环境的重要性。

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