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This paper studies joint design of mixed-timescale hybrid precoding and combining to maximize the effective capacity for wireless backhaul in massive multiple-input multiple-output (MIMO) systems. Specifically, radio frequency (RF) analog processing is adaptive to statistical channel state information (CSI) while digital baseband processing is updated with instantaneous effective CSI. Equipped with...
This paper examines design of mixed-timescale hybrid precoding with vector perturbation (VP) to achieve minimum mean square errors (MMSE) for multi-user massive multiple-input multiple-output (MIMO) systems. In particular, equipped with the perfect effective channel state information (CSI)-based MMSE-VP solution at the baseband, we derive partial CSI-based linear radio frequency (RF) precoding as...
In this paper, we study joint design of linear hybrid precoding and equalization for full-duplex (FD) massive multiple-input multiple-output (MIMO) systems such that the sum mean squared error is minimized across all mobile stations. To better resolve practical issues such as hardware complexity, power consumption, and overhead of channel estimation, hybrid processing, which consists of digital processing...
This paper studies hybrid RF/baseband linear pre-coding design to minimize the mean square error (MSE) for millimeter-wave massive multiple-input multiple-output (MIMO) systems using optimal linear equalizer. Instead of dealing with the objective function of sum MSE, which involves matrix inverses, we approach this problem by minimizing the Euclidean distance between the hybrid precoder and the optimal...
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