J
Jingbo Du
Researcher at Southeast University
Publications - 15
Citations - 150
Jingbo Du is an academic researcher from Southeast University. The author has contributed to research in topics: MIMO & Precoding. The author has an hindex of 3, co-authored 14 publications receiving 77 citations.
Papers
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Journal ArticleDOI
Hybrid Precoding Architecture for Massive Multiuser MIMO With Dissipation: Sub-Connected or Fully Connected Structures?
TL;DR: In this paper, the authors investigated the spectral efficiencies of two typical hybrid precoding structures, i.e., the sub-connected structure and the fully connected structure, under a more realistic hardware network model, particularly, with inevitable dissipation.
Journal ArticleDOI
Hybrid Precoding Architecture for Massive Multiuser MIMO with Dissipation: Sub-Connected or Fully-Connected Structures?
TL;DR: In this paper, the spectral efficiencies of two typical hybrid precoding structures, i.e., the subconnected structure and the fully-connected structure, were investigated over limited feedback channels for massive multiuser MIMO systems.
Journal ArticleDOI
Energy-Saving UAV-Assisted Multiuser Communications With Massive MIMO Hybrid Beamforming
TL;DR: It is shown that the weighted average location could be an approximate method to design the UAV location with little performance gap to the optimal location even when path loss exponent is not 2.
Journal ArticleDOI
Weighted Spectral Efficiency Optimization for Hybrid Beamforming in Multiuser Massive MIMO-OFDM Systems
TL;DR: In this paper, the authors considered hybrid beamforming designs for multiuser massive MIMO-orthogonal frequency division multiplexing (OFDM) systems and proposed one alternating maximization framework where the analog precoding is optimized by Riemannian manifold optimization.
Posted Content
Weighted Spectral Efficiency Optimization for Hybrid Beamforming in Multiuser Massive MIMO-OFDM Systems
TL;DR: This article considers hybrid beamforming designs for multiuser massive multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems and proposes one alternating maximization framework where the analog precoding is optimized by Riemannian manifold optimization.