Calibration of NYURay for Ray Tracing Using 28, 73, and 142 GHz Channel Measurements Conducted in Indoor, Outdoor, and Factory Scenarios

被引:3
作者
Kanhere, Ojas [1 ]
Poddar, Hitesh [1 ]
Rappaport, Theodore S. [1 ]
机构
[1] NYU, NYU WIRELESS Res Ctr, NYU Tandon Sch Engn, Brooklyn, NY 11201 USA
基金
美国国家科学基金会;
关键词
Wireless communication; Ray tracing; Reflection; Wireless sensor networks; Calibration; Time measurement; Millimeter wave communication; Loss measurement; Delays; Production facilities; 5G; 6G; channel modeling; machine learning; mmWave; sub-THz; wireless ray tracing; MILLIMETER-WAVE PROPAGATION; PATH LOSS; WIRELESS COMMUNICATIONS; COMMUNICATION; MODELS; PREDICTION; SCATTERING;
D O I
10.1109/TAP.2024.3472214
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Site-specific wireless channel simulations via ray tracers can be used to effectively study wireless network deployments, decreasing the need for extensive site-specific radio propagation measurements. To ensure that ray tracer simulations faithfully reproduce wireless channels, calibration of simulation results against real-world measurements is required. In this study, we introduce NYURay, a 3-D ray tracer specifically tailored for mmWave and sub-THz frequencies. To reliably generate site-specific wireless channel parameters, NYURay is calibrated using radio propagation measurements conducted at 28, 73, and 142 GHz in diverse scenarios such as outdoor areas, indoor offices, and factories. Traditional ray tracing calibration assumes angle-dependent reflection, requiring slow iterative optimization techniques with no closed-form solution. We propose a simpler and quicker novel calibration method that assumes angle-independent reflection. The effectiveness of the proposed calibration approach is demonstrated using NYURay. When comparing the directional multipath power predicted by NYURay to the actual measured power, the standard deviation in error was less than 3 dB in indoor office environments and less than 2 dB in outdoor and factory environments. The root mean square (rms) delay spread and angular spread were underpredicted by NYURay due to incomplete environmental maps available for calibration; however, an overall agreement between the measured and simulated values was observed. These results highlight the high level of accuracy NYURay provides in generating the site-specific real-world wireless channel, that could be used to generate synthetic data for machine learning.
引用
收藏
页码:405 / 420
页数:16
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