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We investigate the user-to-cell association (or user-clustering) andbeamforming design for Cloud Radio Access Networks (CRANs) and Fog Radio AccessNetworks (FogRANs) for 5G. CRAN enables cloud centralized resource and powerallocation optimization over all the small cells served by multiple AccessPoints (APs). However, the fronthaul links connecting each AP to the cloudintroduce delays and cause outdated Channel State Information (CSI). Bycontrast, FogRAN enables lower latencies and better CSI qualities, at the costof local optimization. To alleviate these issues, we propose a hybrid algorithmexploiting both the centralized feature of the cloud for globally-optimizedpre-scheduling using outdated CSIs and the distributed nature of FogRAN foraccurate beamforming with high quality CSIs. The centralized phase enables toconsider the interference patterns over the global network, while thedistributed phase allows for latency reduction. Simulation results show thatour hybrid algorithm for FogRAN outperforms the centralized algorithm underimperfect CSI, both in terms of throughput and delays.

User Pre-Scheduling and Beamforming with Imperfect CSI in 5G Fog Radio Access Networks