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Standard ray tracing predictions are found to overpredict signal strength in “down the street” scenarios when compared against over 800 urban street measurements on 12 Manhattan streets, nominally Line of Sight (LOS) scenarios, by over 20 dB at 300 m. Use of Uniform Theory of Diffraction (UTD) formulas for around corner cases is found to underpredict signal strength in comparison to observations, with 7.8 dB RMS error. It is found that including effects of scatter from street clutter, such as vegetation and street poles results in simple path loss expressions with RMSE of 7.8 dB for down-street cases and 2.3 dB for around corner.
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This content will become publicly available on May 1, 2026
Around-corner and Over-top 28 GHz measurement in manhattan: Path loss and AoA for MU-MIMO
This paper presents findings from an extensive 28 GHz mmWave measurement campaign conducted in New York City. The study includes over 20 million power measurements collected from two key scenarios: around-corner (non-line-ofsight due to building blockages) and same-street (nominally lineof-sight without obstructions from street furniture or foliage), covering over 1,300 unique links. For urban macro-cell (UMa) rooftop base stations above local clutter, the dominant angle of arrival (AoA) deviates by only 2 to 3.5 degrees from the direct transmitter/receiver direction. This small deviation allows for effective spatial separation between users, facilitating the future development of Multi-User MIMO algorithms for Beyond5G networks. In the urban micro-cell (UMi) dataset, with base stations below local clutter, a path gain drop of over 20 dB was observed in around-corner segments just 20 meters into a corner. Our Street-Clutter-NLOS path loss model achieves an RMSE of 6.4 dB, compared to 11.9 dB from NLOS 3GPP models. Using the best path loss model to estimate coverage for 90% of users traveling around corners, downlink rates could drop by over 10 times after 50 meters, highlighting the challenges in maintaining consistent user experience over mmWave networks in urban street canyons.
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- Award ID(s):
- 2232455
- PAR ID:
- 10655341
- Publisher / Repository:
- in Proc. IEEE INFOCOM’25, 2025
- Date Published:
- Format(s):
- Medium: X
- Location:
- London, UK
- Sponsoring Org:
- National Science Foundation
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