Published October 9, 2022 | Version v1.0
Dataset Open

Propagation Measurements and Analyses at 28GHz on NSF POWDER

  • 1. Arizona State University
  • 2. Purdue University

Contributors

Researcher:

  • 1. Arizona State University
  • 2. Purdue University

Description

IEEE ICC 2023: Propagation Measurements and Analyses at 28GHz via an Autonomous Beam-Steering Platform

 

This paper details the design of an autonomous alignment and tracking platform to mechanically steer directional horn antennas in a sliding correlator channel sounder setup for 28-GHz V2X propagation modeling. A pan-and-tilt subsystem facilitates uninhibited rotational mobility along the yaw and pitch axes, driven by open-loop servo units and orchestrated via inertial motion controllers. A geo-positioning subsystem augmented in accuracy by real-time kinematics enables navigation events to be shared between a transmitter and receiver over an Apache Kafka messaging middleware framework with fault tolerance. Herein, our system demonstrates a 3D geo-positioning accuracy of 17 cm, an average principal axes positioning accuracy of 1.1 degrees, and an average tracking response time of 27.8 ms. Crucially, fully autonomous antenna alignment and tracking facilitates continuous series of measurements, a unique yet critical necessity for millimeter wave channel modeling in vehicular networks. The power-delay profiles, collected along routes spanning urban and suburban neighborhoods on the NSF POWDER testbed, are used in pathloss evaluations involving the 3GPP TR38.901 and ITU M.2135 standards. Empirically, we demonstrate that these models fail to accurately capture the 28-GHz pathloss behavior in urban foliage and suburban radio environments. In addition to RMS direction-spread analyses for angles-of-arrival via the SAGE algorithm, we perform signal decoherence studies wherein we derive exponential characteristics of the spatial autocorrelation coefficient under distance and alignment effects.

Note: This is a smaller version of our dataset. The original dataset collected on the NSF POWDER testbed is approximately 400 GB. Due to Zenodo's size restrictions, the data uploaded here contains only a few of our calibration (USRP 76 dB gain) and measurement logs (fully-autonomous V2X routes onsite). To gain access to our complete dataset, please contact the authors at <bkeshav1@asu.edu> or <zhan1472@purdue.edu>. Additional measurements in our full dataset include USRP 0 dB calibration results; fully-autonomous urban-stadium-van, urban-campus-cart, and urban-presidents-circle-full-van routes; and semi-autonomous (and manual) urban-garage-cart and urban-campus-cart routes.

Notes

This dataset is referenced in our manuscript submission to IEEE ICC 2023.

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Additional details

Related works

Is required by
Software: 10.5281/zenodo.7127320 (DOI)
Is source of
Conference paper: 10.23919/USNC-URSINRSM57467.2022.9881448 (DOI)
Conference paper: arXiv:2110.07106 (arXiv)

References

  • 10.23919/USNC-URSINRSM57467.2022.9881448
  • 10.1109/LWC.2019.2899299
  • 10.1109/ICC.2018.8422820
  • 10.5281/zenodo.7127320