Coverage Analysis for Multi-Request Association Model (MRAM) in a Caching Ultra-Dense Network
Coverage Analysis for Multi-Request Association Model (MRAM) in a Caching Ultra-Dense Network
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DOI：
10.1109/tvt.2019.2896604
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发表时间：
2019-01
影响因子：
6.8
通讯作者：
K. S. Khan;A. Jamalipour
中科院分区：
文献类型：
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作者：
K. S. Khan;A. Jamalipour
研究了基于多请求的用户关联模型对超密集小蜂窝网络性能的影响。我们考虑了一个支持缓存的小蜂窝网络，其中流行文件根据文件的空间流行度被缓存在不同的小蜂窝中。不同于传统的用户向附近单个小区发送请求的模型，我们提出了基于多请求的用户关联模型(MRAM)。在此模型中，用户选择其附近的多个小小区(称为邻居)来发送文件请求。邻居的这个子集同时搜索所请求的文件，以便在小小区级别将其提供给用户。这会提高覆盖概率，从而增加缓存命中率，最终缓解回程拥塞。我们通过考虑不同的覆盖模式来进一步挖掘覆盖概率，并根据这些覆盖场景推导出闭合形式的表达式。我们具体论证了这种多请求模型的性能随着用户在不同区域的移动而提高。通过数值模拟和网络模拟，以覆盖概率的形式量化了从MRAM获得的增益。
This paper examines the impact of multiple requests based user association model on the performance of ultra-dense small cell network. We consider a cache-enabled small cell network where popular files are cached in different small cells according to the spatial popularity of files. Unlike traditional models, where a user sends requests to a single nearby small cell, we propose a multi-request based user association model (MRAM). In this model, a user selects multiple small cells in its vicinity, referred to as neighbors, for sending file requests. This subset of neighbors search the requested file simultaneously, in order to provide it to the user at the small cell level. This results in an improved coverage probability, which increases the cache hit ratio, eventually alleviating the backhaul congestion. We further exploit coverage probability by considering different coverage patterns and derive closed-form expressions based on these coverage scenarios. We concretely demonstrate that the performance of such a multi-request model is improved with user's movement in different regions. Gains obtained from MRAM are quantified in terms of coverage probability through numerical simulations as well as network simulations.