[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Physics-guided characterization and optimization of solar cells using surrogate machine learning model
DOI:10.1109/PVSC40753.2019.8980715
出版年份:2019
更新时间:2025-09-19 17:13:59
摘要:
Multiple transmitting antennas can considerably increase the downlink spectral ef?ciency by beamforming to multiple users at the same time. However, multiuser beamforming requires channel state information (CSI) at the transmitter, which leads to training overhead and reduces overall achievable spectral ef?ciency. In this paper, we propose and analyze a sequential beamforming strategy that utilizes full-duplex base station to implement downlink data transmission concurrently with CSI acquisition via in-band closed or open loop training. Our results demonstrate that full-duplex capability can improve the spectral ef?ciency of uni-directional traf?c, by leveraging it to reduce the control overhead of CSI estimation. In moderate SNR regimes, we analytically derive tight approximations for the optimal training duration and characterize the associated respective spectral ef?ciency. We further characterize the enhanced multiplexing gain performance in the high SNR regime. In both regimes, the performance of the proposed full-duplex strategy is compared with the half-duplex counterpart to quantify spectral ef?ciency improvement. With experimental data and 3-D channel model from 3GPP, in a 1.4 MHz 8 × 8 system LTE system with the block length of 500 symbols, the proposed strategy attains a spectral ef?ciency improvement of 130% and 8% with closed and open loop training, respectively.
作者:
Xu Du,John Tadrous,Ashutosh Sabharwal