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A Caching Strategy Towards Maximal D2D Assisted Offloading Gain

机译:朝向最大D2D辅助卸载增益的缓存策略

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摘要

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.
机译:与内容缓存的设备到设备(D2D)通信被认为是卸载蜂窝流量数据的有希望的方法。在本文中,研究了缓存策略,以通过全面考虑用户协作特性以及物理传输条件来最大化D2D卸载增益。具体而言,对于给定的内容,不同组中感兴趣的用户的数量是不同的,用户始终询问最值得信赖的用户在接近D2D传输。首先导出D2D成功概率的分析表达,这表示接收信号与干扰比的概率不小于给定阈值。由于配制的问题是非耦合,所以特殊的非偏见情况的最佳缓存策略以封闭形式导出,并且提出了一种数值搜索算法来获得常规情况的全局最佳解决方案。为了降低计算复杂性,提出了一种基于D2D成功概率的渐近近似的迭代算法,以获得满足karush-kuhn-tucker条件的解决方案。仿真结果验证了分析结果的有效性,并表明所提出的算法在卸载增益方面优于现有方案。

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