Hybrid Precoding Architecture for Massive Multiuser MIMO with Dissipation: Sub-Connected or Fully-Connected Structures?
arXiv:1806.02857 · doi:10.1109/TWC.2018.2844207
Abstract
In this paper, we study the hybrid precoding structures over limited feedback channels for massive multiuser multiple-input multiple-output (MIMO) systems. We focus on the system performance of hybrid precoding under a more realistic hardware network model, particularly, with inevitable dissipation. The effect of quantized analog and digital precoding is characterized. We investigate the spectral efficiencies of two typical hybrid precoding structures, i.e., the sub-connected structure and the fully-connected structure. It is revealed that increasing signal power can compensate the performance loss incurred by quantized analog precoding. In addition, by capturing the nature of the effective channels for hybrid processing, we employ a channel correlation-based codebook and demonstrate that the codebook shows a great advantage over the conventional random vector quantization (RVQ) codebook. It is also discovered that, if the channel correlation-based codebook is utilized, the sub-connected structure always outperforms the fully-connected structure in either massive MIMO or low signal-to-noise ratio (SNR) scenarios; otherwise, the fully-connected structrue achieves better performance. Simulation results under both Rayleigh fading channels and millimeter wave (mmWave) channels verify the conclusions above.
arXiv comment31 pages, 8 figures, accepted by IEEE Transactions on Wireless Communications
References in corpus (17)
- Massive MIMO for Next Generation Wireless Systems
- Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
- Spatially Sparse Precoding in Millimeter Wave MIMO Systems
- An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems
- Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
- Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems
- Limited Feedback Hybrid Precoding for Multi-User Millimeter Wave Systems
- Low-Complexity Hybrid Precoding in Massive Multiuser MIMO Systems
- Distributed Compressive CSIT Estimation and Feedback for FDD Multi-user Massive MIMO Systems
- Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems
- Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO
- Downlink Training Techniques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training with Memory
- On the Number of RF Chains and Phase Shifters, and Scheduling Design with Hybrid Analog-Digital Beamforming
- Linear Precoding of Data and Artificial Noise in Secure Massive MIMO Systems
- Quantum superintegrability and exact solvability in N dimensions
- MIMO Relaying Broadcast Channels with Linear Precoding and Quantized Channel State Information Feedback
- Hybrid RF and Digital Beamformer for Cellular Networks: Algorithms, Microwave Architectures and Measurements
Cited by in corpus (7)
- Fully-/Partially-Connected Hybrid Beamforming Architectures for mmWave MU-MIMO
- Energy-Efficient Hybrid Precoding for Massive MIMO mmWave Systems With a Fully-Adaptive-Connected Structure
- Analog Versus Hybrid Precoding for Multiuser Massive MIMO with Quantized CSI Feedback
- Low-Complexity On-Grid Channel Estimation for Partially-Connected Hybrid XL-MIMO
- Hybrid Transceiver Optimization for Multi-Hop Communications
- High-Bandwidth Spatial Equalization for mmWave Massive MU-MIMO with Processing-In-Memory
- Weighted Spectral Efficiency Optimization for Hybrid Beamforming in Multiuser Massive MIMO-OFDM Systems