Adaptive training‐feedback scheme for FDD in massive MIMO systems

Accurate acquisition of channel state information (CSI) is crucial but difficult in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems. To improve the estimation accuracy and to minimize training consumption, an adaptive training-feedback scheme based on spatial reciprocity FDD proposed. The main idea this construct a reference frame that matches structure. Reference vectors with strongest correlation uplink are selected design pilots. pilots can adapt changes proposed scheme, which lead substantial reduction feedback overheads. simulation results show under full feedback, throughput approach optimal performance, finite-bit utilization also significantly high less training.