With the rapid explosion of data volume from mobile networks, edge caching has received significant attentions as an efficient approach to boost content delivery efficiency by bringing contents near users. In this article, cache-enabled heterogeneous networks (HetNets) considering the limited backhaul are analyzed with the aid of the stochastic geometry approach. A hybrid caching policy, in which the most popular contents are cached in the macro BSs tier with the deterministic caching strategy and the less popular contents are cached in the helpers tier with the probabilistic caching strategy, is proposed. Correspondingly, the content-centric association strategy is designed based on the comprehensive state of the access link, the cache and the backhaul link. Under the hybrid caching policy, new analytical results for successful content delivery probability, average successful delivery rate and energy efficiency are derived in the general scenario, the interference-limited scenario and the mean load scenario. The simulation results show that the proposed caching policy outperforms the most popular caching policy in HetNets with the limited backhaul. The performance gain is dramatically improved when the content popularity is less skewed, the cache capacity is sufficient and the helper density is relatively large. Furthermore, it is confirmed that there exists an optimal helper density to maximize the energy efficiency of the cache-enabled HetNets.

中文翻译：

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具有有限回程的支持缓存的 HetNet：随机几何模型

随着移动网络数据量的快速增长，边缘缓存作为一种通过将内容带到用户附近来提高内容交付效率的有效方法而受到了极大的关注。在本文中，借助随机几何方法分析了考虑有限回程的支持缓存的异构网络 (HetNets)。提出了一种混合缓存策略，其中最流行的内容使用确定性缓存策略缓存在宏 BS 层，不太受欢迎的内容使用概率缓存策略缓存在助手层。相应地，基于接入链路、缓存和回程链路的综合状态设计了以内容为中心的关联策略。在混合缓存策略下，在一般场景、干扰受限场景和平均负载场景中，推导出成功内容交付概率、平均成功交付率和能源效率的新分析结果。仿真结果表明，所提出的缓存策略在回程有限的情况下优于 HetNets 中最流行的缓存策略。当内容流行度偏小、缓存容量充足、助手密度较大时，性能提升显着。此外，已确认存在最佳辅助密度以最大化启用缓存的 HetNet 的能源效率。仿真结果表明，所提出的缓存策略在回程有限的情况下优于 HetNets 中最流行的缓存策略。当内容流行度偏小、缓存容量充足、助手密度较大时，性能提升显着。此外，已确认存在最佳辅助密度以最大化启用缓存的 HetNet 的能源效率。仿真结果表明，所提出的缓存策略在回程有限的情况下优于 HetNets 中最流行的缓存策略。当内容流行度偏小、缓存容量充足、助手密度较大时，性能提升显着。此外，已确认存在最佳辅助密度以最大化启用缓存的 HetNet 的能源效率。