Hybrid Beamforming for 5G and Beyond Millimeter-Wave Systems: A Holistic View
arXiv:1911.02853
Abstract
Millimeter-wave (mm-wave) communication is a key technology for future wireless networks. To combat significant path loss and exploit the abundant mm-wave spectrum, effective beamforming is crucial. Nevertheless, conventional fully digital beamforming techniques are inapplicable, as they demand a separate radio frequency (RF) chain for each antenna element, which is costly and consumes too much energy. Hybrid beamforming is a cost-effective alternative, which can significantly reduce the hardware cost and power consumption by employing a small number of RF chains. This paper presents a holistic view on hybrid beamforming for 5G and beyond mm-wave systems, based on a new taxonomy for different hardware structures. We take a pragmatic approach and compare different proposals from three key aspects: 1) hardware efficiency, i.e., the required hardware components; 2) computational efficiency of the associated beamforming algorithm; and 3) achievable spectral efficiency, a main performance indicator. Through systematic comparisons, the interplay and trade-off among these three design aspects are demonstrated, and promising candidates for hybrid beamforming in future wireless networks are identified.
arXiv comment14 pages, 10 figures, invited paper submitted to IEEE Open Journal of the Communications Society (OJ-COMS)
References in corpus (14)
- Massive MIMO for Next Generation Wireless Systems
- Spatially Sparse Precoding in Millimeter Wave MIMO Systems
- Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
- Millimeter Wave Cellular Wireless Networks: Potentials and Challenges
- Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems
- Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays
- Low-Complexity Hybrid Precoding in Massive Multiuser MIMO Systems
- Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems
- Compressed Sensing Based Multi-User Millimeter Wave Systems: How Many Measurements Are Needed?
- Spatial Deep Learning for Wireless Scheduling
- Hybrid Beamforming for Millimeter Wave Systems Using the MMSE Criterion
- On the Number of RF Chains and Phase Shifters, and Scheduling Design with Hybrid Analog-Digital Beamforming
- A Hardware-Efficient Analog Network Structure for Hybrid Precoding in Millimeter Wave Systems
- Bayesian Optimal Data Detector for Hybrid mmWave MIMO-OFDM Systems with Low-Resolution ADCs