4.3 Article

Performance analysis of cache-enabled wireless networks considering stochastic geometry approach

期刊

IET COMMUNICATIONS
卷 13, 期 8, 页码 1043-1050

出版社

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-com.2018.5249

关键词

telecommunication network reliability; stochastic processes; Monte Carlo methods; cellular radio; telecommunication traffic; cache storage; probability; multi-access systems; independent Poisson point processes; Matern hard core point process; clustered dense helper nodes; cache-enabled wireless networks; stochastic geometry approach; local nodes; network data traffic; access points; cellular networks; local storages; Monte Carlo simulations; outage probability

资金

  1. IPM
  2. Iran National Science Foundation [95824827]

向作者/读者索取更多资源

Caching of the popular content in the storages of local nodes near to the users has been proposed as a promising approach to handle the network data traffic and the backhaul constraint of access points in the cellular networks. These local storages, also called caches or helpers nodes, are the nodes with the limited communication range but with considerable storage capacities which are generally established condensed to realise the above goals. This dense distribution makes possible the collaboration among the helper nodes for exchanging their embedded files and delivery of the requested files to the users. In this study, to manage the traffic in smaller areas and also to establish more users' accesses to their requested files, clustered dense helper scenario is considered. More precisely, the helper nodes are grouped in disjoint clusters, through the clustering strategy induced by Matern hard core point process. Then the closed-form expressions based on stochastic geometry are derived for some performance metrics of the network. The analytical derivations are validated with Monte Carlo simulations which also compare two cases of clustered dense helper nodes and fewer helper nodes without clustering scenarios. The results show the advantage of the former from the outage probability perspective.

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