基于认知小蜂窝的异构无线网络负载估计与均衡

Man Su, C. Foh, R. Tafazolli
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引用次数: 1

摘要

异构无线网络(HetNet)是增加网络容量的解决方案之一,它由宏蜂窝和在同一区域内大规模部署的小蜂窝组成。认知小单元为HetNets提供了一个有吸引力的解决方案,可以最大限度地减少宏单元和小单元之间的协调需求。在异构无线网络中,将用户与宏单元和小单元充分关联是实现负载平衡的关键,尤其是那些具有认知小单元的网络。本文提出了一种基于认知小单元的HetNets负载均衡方案。我们的方案使用基于模型的解决方案来估计认知小单元中活动用户数量测量的负载,并在宏单元和小单元之间平衡负载以避免小单元中的拥塞。通过仿真验证了基于模型的解决方案的准确性和有效性。
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Load estimation and balancing in heterogeneous wireless networks with cognitive small cells
A heterogeneous wireless network (HetNet) that consist of macro cells and massively deployed small cells within the same region is one of the solutions to increase network capacity. Cognitive small cells offer an attractive solution for HetNets to minimize the need for coordination between the macro and the small cells. Adequately associating users to the macro and the small cells is critical in heterogeneous wireless networks for load balancing, especially those with cognitive small cells. Ih this paper, we develop a scheme for load balancing in HetNets with cognitive small cells. Our scheme uses a model-based solution to estimate the load measured by the number of active users in cognitive small cells and balances load between the macro and small cells to avoid congestion in small cells. We use simulation to show the accuracy of our model-based solution and effectiveness of our solution.
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