Due to the prosperity of online media, caching video content has become an important measure to improve the user experience and alleviate the link burden in wireless caching networks. However, facing to perceptual requirements of video users, Scalable Video Coding (SVC) technique has been cumulatively utilized in wireless caching networks, which can guarantee acceptable video quality. In this paper, we propose a smart collaborative video caching policy to boost energy efficiency (EE) in Cognitive Content Centric networking (C-CCN), where the spectrum sharing characteristic of cognitive ratio (CR) is integrated into CCN. With consideration of the imperfect channel-state information (CSI), the collision interference exists between the primary users (PUs) and secondary base stations (SBs). Inspired by this, we derive the expressions of successful content delivery rate (SCDR) and total power consumption for the proposed policy. By using these expressions, the optimal EE model under the caching size constraint is formulated as an optimal content placement problem, which can be solved by the standard gradient projection method. Numerical and simulation results show the efficacy and superiority of the proposed policy compared with some traditional caching schemes.

由于在线媒体的繁荣，缓存视频内容已成为改善用户体验并减轻无线缓存网络中链路负担的重要措施。但是，面对视频用户的感知需求，可扩展视频编码（SVC）技术已在无线缓存网络中得到了累积利用，可以保证可接受的视频质量。在本文中，我们提出了一种智能协作视频缓存策略，以在认知内容中心网络（C-CCN）中提高能效（EE），其中将认知比率（CR）的频谱共享特性集成到CCN中。考虑到不完美的信道状态信息（CSI），主要用户（PU）和辅助基站（SB）之间存在冲突干扰。受此启发，我们推导了拟议策略的成功内容交付率（SCDR）和总功耗的表达式。通过使用这些表达式，将在缓存大小约束下的最佳EE模型表述为最佳的内容放置问题，可以通过标准梯度投影方法解决该问题。数值和仿真结果表明，与某些传统的缓存方案相比，该策略的有效性和优越性。