We investigate the user-to-cell association (or user-clustering) and beamforming design for Cloud Radio Access Networks (CRANs) and Fog Radio Access Networks (FogRANs) for 5G. CRAN enables cloud centralized resource and power allocation optimization over all the small cells served by multiple Access Points (APs). However, the fronthaul links connecting each AP to the cloud introduce delays and cause outdated Channel State Information (CSI). By contrast, FogRAN enables lower latencies and better CSI qualities, at the cost of local optimization. To alleviate these issues, we propose a hybrid algorithm exploiting both the centralized feature of the cloud for globally-optimized pre-scheduling using outdated CSIs and the distributed nature of FogRAN for accurate beamforming with high quality CSIs. The centralized phase enables to consider the interference patterns over the global network, while the distributed phase allows for latency reduction. Simulation results show that our hybrid algorithm for FogRAN outperforms the centralized algorithm under imperfect CSI, both in terms of throughput and delays.