A Prefiltering C-RAN Architecture with Compressed Link Data Rate in Massive MIMO

Massive multiple-input multiple-output (MIMO) is a promising technology in the next 5G communications. Directly merging massive MIMO with cloud radio access network (C-RAN) systems will cause disastrous link data overload, which greatly exceeds the limitation of current 4G wireless standards. To solve this problem, we propose a pre-filtering C-RAN architecture in this paper to compress the inter connection link data rate between remote radio units (RRUs) and baseband units (BBUs), which is based on the structure of linear data detection algorithms and able to achieve lossless performance if perfect channel information (CSI) can be acquired. To make the pre-filtering architecture feasible in practical environments, we further propose two channel estimation methods. One using demodulation reference signal (DMRS) can achieve the data rate compression without performance loss, while the other using sounding reference signal (SRS) can keep the thin structures of RRUs as much as possible. Analysis on practical systems and simulation results show that the proposed architecture can provide a better trade off between hardware implementation cost, system performance and traffic load reduction than conventional architectures.