3,472 research outputs found
Design Guidelines for Training-based MIMO Systems with Feedback
In this paper, we study the optimal training and data transmission strategies
for block fading multiple-input multiple-output (MIMO) systems with feedback.
We consider both the channel gain feedback (CGF) system and the channel
covariance feedback (CCF) system. Using an accurate capacity lower bound as a
figure of merit, we investigate the optimization problems on the temporal power
allocation to training and data transmission as well as the training length.
For CGF systems without feedback delay, we prove that the optimal solutions
coincide with those for non-feedback systems. Moreover, we show that these
solutions stay nearly optimal even in the presence of feedback delay. This
finding is important for practical MIMO training design. For CCF systems, the
optimal training length can be less than the number of transmit antennas, which
is verified through numerical analysis. Taking this fact into account, we
propose a simple yet near optimal transmission strategy for CCF systems, and
derive the optimal temporal power allocation over pilot and data transmission.Comment: Submitted to IEEE Trans. Signal Processin
A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels
In this paper, we establish a general framework on the reduced dimensional
channel state information (CSI) estimation and pre-beamformer design for
frequency-selective massive multiple-input multiple-output MIMO systems
employing single-carrier (SC) modulation in time division duplex (TDD) mode by
exploiting the joint angle-delay domain channel sparsity in millimeter (mm)
wave frequencies. First, based on a generic subspace projection taking the
joint angle-delay power profile and user-grouping into account, the reduced
rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived
for spatially correlated wideband MIMO channels. Second, the statistical
pre-beamformer design is considered for frequency-selective SC massive MIMO
channels. We examine the dimension reduction problem and subspace (beamspace)
construction on which the RR-MMSE estimation can be realized as accurately as
possible. Finally, a spatio-temporal domain correlator type reduced rank
channel estimator, as an approximation of the RR-MMSE estimate, is obtained by
carrying out least square (LS) estimation in a proper reduced dimensional
beamspace. It is observed that the proposed techniques show remarkable
robustness to the pilot interference (or contamination) with a significant
reduction in pilot overhead
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