The rapid growth of mobile data traffic, especially video streaming traffic, places a serious burden on cellular networks. D2D caching has emerged as a promising paradigm to alleviate network congestions, in which contents are cached at user terminals proactively and then shared among neighbor requesting users via D2D communications. In this paper, we study the content placement problem to maximize cache hit probability (i.e., the probability that contents requested by users are successfully served by neighbor helpers through D2D communications) in D2D underlaid cellular networks. To decide where to cache and which contents to be pushed, we formulate our problem considering D2D communication probability of helpers and preference probability of requesting users. Then our problem is proved to be a submodular function maximization problem under a matroid constraint. To solve this problem, we present an improved greedy algorithm which can achieve an approximation guarantee of \({\min \limits } (1, \linebreak \frac {1}{v_{0}+\frac {1}{t_{min}}} )\), based on the classic \(\frac {1}{2}\)-approximation algorithm. Simulation results show that our proposed scheme achieves higher cache hit probability and lower energy consumption compared with existing caching schemes.

中文翻译：

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D2D底层蜂窝网络中的最佳内容放置

移动数据流量（尤其是视频流流量）的快速增长给蜂窝网络带来了沉重的负担。D2D缓存已成为缓解网络拥塞的一种有希望的范例，其中内容被主动缓存在用户终端，然后通过D2D通信在相邻的请求用户之间共享。在本文中，我们研究了D2D底层蜂窝网络中的内容放置问题，以最大程度地提高缓存命中率（即，用户请求的内容被D2D通信成功地由邻居助手成功提供的概率）。为了决定在哪里缓存以及要推送哪些内容，我们考虑了辅助者的D2D通信概率和请求用户的偏好概率来制定问题。然后证明了我们的问题是拟阵约束下的子模函数最大化问题。为了解决这个问题，我们提出了一种改进的贪婪算法，该算法可以实现\（{\ min \ limits}（1，\ linebreak \ frac {1} {v_ {0} + \ frac {1} {t_ {min}}}）\），基于经典\（\ frac {1 } {2} \） -近似算法。仿真结果表明，与现有的缓存方案相比，该方案具有更高的缓存命中率和更低的能耗。