Low-complexity massive MIMO scheduling via DFT of correlation functions and correlation-matrix-based precoding maintains near-optimal throughput with major complexity reduction under the COST 2100 model, even without CSIT.
A New Approach to User Scheduling in Massive Multi-User MIMO Broadcast Channels
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abstract
In this paper, a new user-scheduling-and-beamforming method is proposed for multi-user massive multiple-input multiple-output (massive MIMO) broadcast channels in the context of two-stage beamforming. The key ideas of the proposed scheduling method are 1) to use a set of orthogonal reference beams and construct a double cone around each reference beam to select `nearly-optimal' semi-orthogonal users based only on channel quality indicator (CQI) feedback and 2) to apply post-user-selection beam refinement with zero-forcing beamforming (ZFBF) based on channel state information (CSI) feedback only from the selected users. It is proved that the proposed scheduling-and-beamforming method is asymptotically optimal as the number of users increases. Furthermore, the proposed scheduling-and-beamforming method almost achieves the performance of the existing semi-orthogonal user selection with ZFBF (SUS-ZFBF) that requires full CSI feedback from all users, with significantly reduced feedback overhead which is even less than that required by random beamforming.
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Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions
Low-complexity massive MIMO scheduling via DFT of correlation functions and correlation-matrix-based precoding maintains near-optimal throughput with major complexity reduction under the COST 2100 model, even without CSIT.