PROJECT TITLE :

Joint Optimization of Hybrid Beamforming for Multi-User Massive MIMO Downlink - 2018

ABSTRACT:

Considering the design of 2-stage beamformers for the downlink of multi-user massive multiple-input multiple-output systems in frequency division duplexing mode, this Project investigates the case where each the link ends are equipped with hybrid digital/analog beamforming structures. A virtual sectorization is realized by channel-statistics-primarily based user grouping and analog beamforming, where the user equipment solely wants to feedback its intra-cluster effective channel, and the value of channel state info (CSI) acquisition is considerably reduced. Underneath the Kronecker channel model assumption, we have a tendency to 1st show that the strongest eigenbeams of the receive correlation matrix kind the optimal analog combiner to maximise the intra-group signal to inter-cluster interference plus noise ratio. Then, with the partial data of instantaneous CSI, we jointly optimize the digital precoder and combiner by maximizing a lower bound of the conditional average internet total rate. Simulations over the propagation channels obtained from geometric-primarily based stochastic models, ray tracing results, and measured out of doors channels, demonstrate that our proposed beamforming strategy outperforms the state-of-the-art ways.


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