OFDMA宏飞蜂窝网络中飞蜂窝聚类的联合对策

Katty Rohoden, Rebeca L. Estrada, H. Otrok, Z. Dziong
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引用次数: 6

摘要

本文研究了宏蜂窝网络中的资源管理问题。密集部署的移动基站给基于集群的资源分配带来了一些挑战。其中一些挑战是在宏蜂窝的卸载流量水平和分配给飞层的带宽之间进行权衡、公平分配资源以及减轻集群间干扰。为了克服这些限制,我们提出了一种联合博弈来形成飞蜂窝集群,从而降低资源分配的复杂性。稳定的集群是基于核心模型形成的。我们的建议主要由三个部分组成。即针对公共用户的移动基站选择,合作的移动基站获得奖励的联盟博弈,以及分配资源的加权充水算法。我们的解是在一个基于理想光谱效率和有效光谱效率的奖励模型下进行的。我们比较了我们的奖励模型和非合作模型的结果,其中飞基站工作在封闭访问模式。仿真结果表明,该方案提高了飞层吞吐量和用户满意度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A coalitional game for femtocell clustering in OFDMA macro-femtocell networks
In this paper, we tackle the problem of resource management in macro-femtocell networks. Dense deployment of femtocells imposes several challenges for a cluster-based resource allocation. Some of those challenges are the trade-off between the level of offloaded traffic from macrocell and bandwidth allocated to femto-tier, the fair distribution of resources, and the mitigation of inter-cluster interference. To overcome these limitations, we propose a coalitional game to form clusters of femtocells that can reduce the resource allocation complexity. Stable clusters are formed based on the core model. Our proposal mainly consists of three components. Namely, a femtocell selection for public users, a coalitional game where cooperative femtocells are rewarded, and a Weighted Water Filling algorithm to allocate resources. Our solution is performed under a rewarding model, which is based on an ideal spectral efficiency and on an effective spectral efficiency. We compare the results of our rewarding model with a non-cooperative model, where femtocells work in closed access mode. Simulation results demonstrate that our proposal improves the femto-tier throughput and the satisfaction of femtocells subscribers.
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