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Spectral and Energy Efficiencies of Millimeter Wave MIMO With Configurable Hybrid Precoding
1Advanced Network Technologies Division, National Institute of Standards and Technology, Gaithersburg, MD 20899 USA. He is now with the School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
This study explores hybrid precoding in millimeter wave (mmWave) massive MIMO systems, optimizing RF chain activation for spectral and energy efficiency. Results show distinct optimal configurations for high and low signal-to-noise ratios (SNRs), with single RF chain analog beamforming being optimal for low SNRs.
Area of Science:
- Wireless communication systems
- Signal processing for telecommunications
- Antenna array design
Background:
- Hybrid precoding is crucial for millimeter wave (mmWave) massive MIMO systems.
- Practical constraints on RF chains significantly impact system efficiency.
- Optimizing RF chain usage is key to balancing spectral and energy efficiency.
Purpose of the Study:
- Investigate the tradeoff between spectral and energy efficiency in hybrid precoding.
- Analyze performance in static and mobile communication scenarios.
- Develop methods for adaptive RF chain activation based on channel conditions.
Main Methods:
- Derivation of closed-form expressions for performance metrics.
- Analysis of hybrid precoding with selectable active RF chains.
- Evaluation of mobility-aware hybrid precoding strategies.
Main Results:
- Optimal RF chain configurations differ for maximizing spectral vs. energy efficiency at high SNRs.
- Single RF chain analog beamforming is optimal for both efficiencies at low SNRs.
- Proposed mobility-aware approach effectively achieves beamforming gain for high-speed mobile devices.
Conclusions:
- Adaptive RF chain activation reduces computational complexity for hybrid precoder configuration.
- System design must consider SNR levels and mobility for optimal performance.
- The study provides insights into efficient resource allocation in mmWave massive MIMO systems.
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