This paper studies the caching system of multiple cache-enabled users with random demands. Under nonuniform file popularity, we thoroughly characterize the optimal uncoded cache placement structure for the coded caching scheme (CCS). Formulating the cache placement as an optimization problem to minimize the average delivery rate, we identify the file group structure in the optimal solution. We show that, regardless of the file popularity distribution, there are \emph{at most three file groups} in the optimal cache placement{, where files within a group have the same cache placement}. We further characterize the complete structure of the optimal cache placement and obtain the closed-form solution in each of the three file group structures. A simple algorithm is developed to obtain the final optimal cache placement by comparing a set of candidate closed-form solutions computed in parallel. We provide insight into the file groups formed by the optimal cache placement. The optimal placement solution also indicates that coding between file groups may be explored during delivery, in contrast to the existing suboptimal file grouping schemes. Using the file group structure in the optimal cache placement for the CCS, we propose a new information-theoretic converse bound for coded caching that is tighter than the existing best one. Moreover, we characterize the file subpacketization in the CCS with the optimal cache placement solution and show that the maximum subpacketization level in the worst case scales as $\mathcal{O}(2^K/\sqrt{K})$ for $K$ users.
翻译:本文研究有随机需求的多个缓存驱动用户的缓存系统 。 在不统一的文件受欢迎度下, 我们彻底描述编码缓存机制( CCS) 的最佳未编码缓存放置结构。 将缓存放置作为优化交付率的最优化问题, 我们在最佳解决方案中确定文件组结构。 我们显示, 无论文件的流行性分布如何, 在最佳缓存放置{ 最多三个文件组} 中, 在一个组内的文件有相同的缓存位置} 的最佳缓存位置 。 我们进一步描述最佳缓存放置的完整结构, 并在三个文件组结构的每一个结构中获得封闭式的缓存设置。 开发了一个简单的算法, 以通过比较一组平行计算的候选人封闭式解决方案来获得最终的最佳缓存位置。 我们为最佳缓存位置位置所形成的文件组提供了洞察力。 最佳放置解决方案还表明, 文件组之间可以进行编码, 与现有最优的文件组配置相比, 我们提议用一个新的信息- QQQxxxxxxxxx K 格式, 将最佳的缓存卡质化为我们目前的最佳 K 的软化的软化 。