Multi-link cache data retrieval for delivery phase in ultra dense small cell networks

K. S. Khan, Saud Khan, A. Jamalipour
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引用次数: 4

Abstract

Smart user association methods can have tremendous advantages when it comes to caching. It is anticipated that, in future, small cell deployment will be such that there will be at least one small cell for every user. This comes with a great advantage of maximizing the hit probability for cache-enabled networks. In this work, we investigate a multi-link user association model for Ultra Dense Networks (UDN) in which a user associates with multiple caching entities to retrieve its requested content. The user has a chance to search for the requested file at multiple locations, which will increase the chances of getting the request fulfilled, subsequently increasing the cache hit ratio of the user. We let the user select its preferences based on the received SINR from the available caches and leverage the basic user association methods to fully exploit the resources available to the user. Consequently, we derive analytical expressions to study the data rate and achieved cache hit ratio by the proposed method. Through simulation results, we illustrate that the performance of our proposed multi-link cache data retrieval method is distinctively different from present schemes and shed new insight on serving users in a cache-enabled UDN.
超密集小蜂窝网络传输阶段的多链路缓存数据检索
当涉及到缓存时,智能用户关联方法具有巨大的优势。预计在未来,小型蜂窝部署将是这样的:每个用户至少有一个小型蜂窝。这带来了一个巨大的优势,可以最大化启用缓存的网络的命中概率。在这项工作中,我们研究了超密集网络(UDN)的多链路用户关联模型,其中用户与多个缓存实体关联以检索其请求的内容。用户有机会在多个位置搜索所请求的文件,这将增加请求得到满足的机会,随后增加用户的缓存命中率。我们让用户根据从可用缓存中接收到的SINR选择首选项,并利用基本的用户关联方法来充分利用用户可用的资源。因此,我们推导出解析表达式来研究数据速率,并通过所提出的方法获得缓存命中率。通过仿真结果,我们说明了我们提出的多链路缓存数据检索方法的性能与现有方案明显不同,并为在启用缓存的UDN中为用户服务提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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