带有特征感知的D2D内容缓存策略

设备到设备通信(D2D)可以有效地卸载基站流量，在D2D网络中不仅需要共享大众化内容还需要个性化内容缓存。该文对缓存内容选择问题进行了深入研究，提出一种结合特征感知的内容社交价值预测(CSVP)方法。价值预测不仅可以降低时延也可以减少缓存替换次数降低缓存成本。首先结合用户特征和内容特征计算内容当前价值，然后通过用户社交关系计算未来价值。微基站根据内容的价值为用户提供个性化内容缓存服务，宏基站则在每个微基站的缓存内容中选择价值较大部分的内容。仿真结果表明，该文提出的缓存策略可以有效缓解基站流量，与其他方法相比降低时延约20%～40%。

Feature-Aware D2D Content Caching Strategy

Device to Device (D2D) communications can effectively offload base station traffic. In D2D networks, the popular content is not only needs to be shared, but also the individual content is needs to be cached. In this paper, the problem of cache content selection is researched. A Content Social Value Prediction(CSVP) method based on feature perception is proposed. Value prediction can not only reduce latency, but also reduce the number of cache replacements and reduce cache costs. Firstly, the current value of content is calculated by combining user features and content features, and then future value is calculated through user social relationships. The small base station provides the user with a personalized content caching service according to the value of the content, and the base station selects a content with a larger value in the individual cache content of each small base station as popular content. Simulation results show that the caching strategy based on the proposed method can alleviate the base station traffic effectively, and reduce the delay by about 20%～40%.