Coded caching (CC) techniques have been shown to be conveniently applicable in multi-input multi-output (MIMO) systems. In a $K$-user network with spatial multiplexing gains of $L$ at the transmitter and $G$ at every receiver, if each user can cache a fraction $\gamma$ of the file library, a total number of $GK\gamma + L$ data streams can be served in parallel. In this paper, we focus on improving the finite-SNR performance of MIMO-CC systems. We first consider a MIMO-CC scheme that relies only on unicasting individual data streams, and then, introduce a decomposition strategy to design a new scheme that delivers the same data streams through multicasting of $G$ parallel codewords. We discuss how optimized beamformers could be designed for each scheme and use numerical simulations to compare their finite-SNR performance. It is shown that while both schemes serve the same number of streams, multicasting provides notable performance improvements. This is because, with multicasting, transmission vectors are built with fewer beamformers, leading to more efficient usage of available power resources.
翻译:编码缓存(CC)技术被证明很方便地适用于多投入多输出系统(MIMO) 。 在以美元计算的用户网络中,如果每个用户都能在文件库中隐藏一小部分美元=gamma + L$的数据流,那么每个用户都可以同时使用文件库中的数据流。在本文中,我们的重点是改进IMO-CC系统有限的SN性能。我们首先考虑只依靠单项数据流的解析的MSIM-CC计划,然后引入一个分解战略,设计一个通过多播以$G的平行代码词提供相同数据流的新计划。我们讨论如何为每个方案设计最佳的光谱,并使用数字模拟来比较其有限-SNR的性能。我们发现,虽然这两种计划都服务于相同数量的流,但多投放提供了显著的性能改进。这是因为,多播式播载矢量的矢量在构建上,使用效率更低的能量资源。