Low-rank preconditioner from top eigenpairs of the covariance matrix via randomized EVD with QRC, applied in beamspace, reduces CG iterations by 2-3x for long-term beamforming while matching exact inversion SINR.
Beamspace mimo for high-dimensional mul- tiuser communication at millimeter-wave frequencies
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Long-term beamforming projection matrices can be optimally computed via matrix inverse square root to maximize capacity bounds, yielding near-instantaneous MMSE performance with far lower overhead in rural uplink ray-tracing simulations.
citing papers explorer
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Low-rank Preconditioning in Beamspace Domain For Massive MU-MIMO Long-Term Beamforming
Low-rank preconditioner from top eigenpairs of the covariance matrix via randomized EVD with QRC, applied in beamspace, reduces CG iterations by 2-3x for long-term beamforming while matching exact inversion SINR.
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Scalable Long-Term Beamforming for Massive Multi-User MIMO
Long-term beamforming projection matrices can be optimally computed via matrix inverse square root to maximize capacity bounds, yielding near-instantaneous MMSE performance with far lower overhead in rural uplink ray-tracing simulations.