EnergyEfficient MixedTimescale Hybrid Precoding for Multiuser Massive MIMO Systems Considering the huge training cost and feedback overhead of wireless communication system where base station is equipped with largescale antenna array, an energyefficient mixedtimescale hybrid precoding is proposed in this paper. The design of hybrid precoding is decoupled, where analog precoder and digital precoder are determined by secondorder statistical channel state information (CSI) and instantaneous CSI respectively. Moreover, for analog precoding, a fixed subconnected architecture is considered to further reduce the hardware complexity and power consumption. It transforms the optimization of analog precoding matrix into lowdimensional problems. Meanwhile, a twostep heuristic method is proposed to obtain nearoptimal solution. Simulation results show that our proposed scheme has a good tradeoff between performance and hardware complexity, power consumption for massive MIMO.

Energy and SpectralEfficiency Tradeoff in Beam Domain Massive MIMO Downlink with Statistical CSIT We investigate energy and spectralefficiency tradeoff by optimizing resource efficiency (RE) for singlecell massive multipleinput multipleoutput (MIMO) downlink transmission with only statistical channel state information available at the transmitter (CSIT). We first show that beam domain transmission is favorable for RE optimization in massive MIMO downlink, by deriving a closedform solution for the eigenvectors of the optimal transmit covariance matrices. With this conclusion, the RE optimization precoding design is reduced to a realvalued power allocation problem. Exploiting sequential optimization and random matrix theory, we further propose a lowcomplexity twolayer waterfillingstructured power allocation algorithm. Numerical results demonstrate the effectiveness of our proposed statistical CSI aided RE optimization approach.