Scenario 2 is a synthetic street-level urban canyon scenario with mobile vehicles, ray-traced channels at 2.8; 5 GHz (2 versions). In this scenario, the base station antenna is positioned at 4m height from the surface making the link more vulnerable to dynamic blockages (buses, trucks) and cornering. Rosslyn urban scenario is configured in 2.8; 5 GHz (2 versions), with 200 episodes of 10 scenes each, time between scenes of 5ms, time between episodes of 37s, 10 fixed receivers and 1 fixed transmitter. The images 1-3 show the 3D meshes of scenario in blender, the SUMO view of maped street where the vehicles realize their routs, the top view of scenario (constructions in yellow, sparce foliage in light green, dense foliage in dark green, ground in baby blue, receivers in red, transmitter in green) at Wireless Insite, respectively.


Rosslyn Avenue (Arlington, VA – Approx. Lat/Long: 38.8950° N, 77.0715° W)is located in the dense urban core of Rosslyn, Arlington, VA, forming part of a grid of narrow streets surrounded by mid- and high-rise buildings. The modeled portion of the avenue in this scenario is a two-way urban street with no marked lanes (common in narrower segments of the Rosslyn district). The effective road width is approximately 8–10 meters, supporting slow, mixed traffic flow. The typical speed limit ranges from 25 to 30 mph (≈ 40–48 km/h), characteristic of urban business districts with frequent intersections and pedestrian activity. Traffic is composed of cars, SUVs, delivery vans, buses, and occasional trucks, all of which introduce diverse mobility patterns and dynamic blockages. From a wireless communication perspective, the absence of lane markings, combined with the narrow street geometry and tall surrounding buildings, produces a pronounced urban canyon effect. Vehicles moving close to the base station line-of-sight can create partial or complete blockages, while buildings generate significant multipath via reflections and diffractions. These characteristics make Rosslyn Avenue a challenging and representative environment for evaluating beam tracking, blockage prediction, and mmWave/6G communication robustness.


The collected data was obtained by simulating traffic at Simulator of Urban Mobility (SUMO) and orchestrating placement and raytracing simulation at wireless Insite (WI) through the python orchestrator Raymobtime. The data collected is described as follows.

1. Ray tracing data: top 100 rays of highest received power, obtained from Wireless Insite (WI).

  • Received power, time of arrival, elevation angle of departure, azimuth angle of departure, elevation angle of arrival, azimuth angle of arrival, LOS condition.
  • Type data: .hdf5 of each episode
  • Processed RUN’s folder: Contains all simulated sampples at Wireless Insite.

Raymobtime Scenario 14 – V2I Rosslyn 60 GHz

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