Recently, the cloud radio access network (C-RAN) architecture has been proposed to enhance the cost effectiveness and flexibility of traditional cell-centric radio access networks. However, the massive fronthaul bandwidth required to centralize baseband computations in C-RAN results in extremely high costs. This paper summarizes our previous efforts toward solving this problem. We proposed the software-defined hyper-cellular network (SDHCN) based on the control/data separation principle. Under the proposed SDHCN framework, we studied two mechanisms that can greatly reduce fronthaul costs through the joint deployment of communicational and computational resources. First, we quantitatively characterized the relationship between the size of virtual base station (VBS) pools and the gains from computational statistical multiplexing by using queueing theory. We then showed that the marginal gain diminishes quickly with a growing pool size. Therefore, it is most economical to deploy mid-sized VBS pools. Finally, we proposed a genetic algorithm for baseband function splitting within a graph-clustering framework. This algorithm provides splitting schemes that can flexibly achieve different tradeoffs between fronthaul and computational costs based on different design preferences.