Device-to-Device (D2D) communications incorporated with content caching have been regarded as a promising way to offload the cellular traffic data. In this paper, the caching strategy is investigated to maximize the D2D offloading gain with the comprehensive consideration of user collaborative characteristics as well as the physical transmission conditions. Specifically, for a given content, the number of interested users in different groups is different, and users always ask the most trustworthy user in proximity for D2D transmissions. An analytical expression of the D2D success probability is first derived, which represents the probability that the received signal to interference ratio is no less than a given threshold. As the formulated problem is nonconvex, the optimal caching strategy for the special unbiased case is derived in a closed form, and a numerical searching algorithm is proposed to obtain the globally optimal solution for the general case. To reduce the computational complexity, an iterative algorithm based on the asymptotic approximation of the D2D success probability is proposed to obtain the solution that satisfies the Karush-Kuhn-Tucker conditions. The simulation results verify the effectiveness of the analytical results and show that the proposed algorithm outperforms the existing schemes in terms of offloading gain.

中文翻译：

---

实现最大 D2D 辅助卸载增益的缓存策略

与内容缓存相结合的设备到设备 (D2D) 通信已被视为卸载蜂窝流量数据的有前途的方式。在本文中，综合考虑用户协作特性和物理传输条件，研究缓存策略以最大化D2D卸载增益。具体来说，对于给定的内容，不同群组中感兴趣的用户数量是不同的，用户总是询问附近最值得信赖的用户进行D2D传输。首先推导出D2D成功概率的解析表达式，它表示接收信号干扰比不小于给定阈值的概率。由于公式化的问题是非凸的，特殊无偏情况的最优缓存策略以封闭形式导出，并提出了一种数值搜索算法，以获得一般情况下的全局最优解。为了降低计算复杂度，提出了一种基于D2D成功概率渐近逼近的迭代算法，以获得满足Karush-Kuhn-Tucker条件的解。仿真结果验证了分析结果的有效性，表明该算法在卸载增益方面优于现有方案。