Ojas Kanhere’s research while affiliated with New York University and other places

The vast bandwidth available at millimeter wave (mmWave) and terahertz (THz) frequencies will allow future 6G wireless networks to support ubiquitous and extremely accurate localization and environmental sensing. Prior geometric localization algorithms typically assume single bounce reflections. This paper describes map-assisted positioning with angle and time (MAP-AT), a novel map-based localization algorithm that takes into account multi-bounce reflections, utilizing the angle of arrival and time of flight of multipath signal components to determine the position of a user. The accuracy of MAP-AT is tested against indoor and factory measurement data at mmWave (28 GHz, 60 GHz) and sub-THz (140 GHz) frequencies. Using a single base station as reference, sub-meter accuracy was achieved at mmWave frequencies, and centimeter-level accuracy was achieved at sub-THz frequencies. Accuracy was improved when more base stations were used. Additionally, the performance of sub-Thz signals for sensing objects behind walls is studied by detecting hidden objects behind plywood and drywall in a laboratory environment, with centimeter-level sensing accuracy and identification of hidden objects successfully achieved. This work shows that the high penetration loss of walls and obstructions at sub-THz frequencies poses a challenge to accurate sensing at sub-THz frequencies. Future work is required to sense objects hidden tens of meters behind walls.

Site-specific wireless channel simulations via ray tracers can be used to effectively study wireless, 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 3D 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 was 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.

A comprehensive understanding of outdoor urban radio propagation at mmWave and sub-THz frequencies is crucial for enabling novel applications such as wireless cognition, precise position-location, and sensing. This paper summarizes extensive measurements and statistical analysis of outdoor radio propagation data collected in New York City between 2012 and 2021 to formulate a multi-band empirical 3-D statistical channel model (SCM) for outdoor urban open squares and streets. Path loss models and SCMs are derived from over 21000 power delay profiles (PDP) measured in Brooklyn and Manhattan. Analysis of multipath components in PDPs reveal underlying statistical distributions for wireless channel parameters, including number of time-clusters (TC), subpaths in TCs, delays and powers of TCs and subpaths, and spatial-cluster directions. Observations at 142 GHz suggest a sparse channel as subpaths in TCs are exponentially distributed with narrower spread spatial-clusters and higher Ricean K-factor, unlike uniform distributions at 28 and 73 GHz. The proposed SCMs at 142, 73, and 28 GHz extend the open-source NYUSIM channel simulator into sub-THz bands up to 150 GHz. The SCMs can aid in designing modems, antenna arrays, beamforming, and spatial multiplexing approaches, while providing an empirical baseline for propagation simulation and prediction tools, such as ray tracers.

Site-specific wireless channel simulations via ray tracers can be used to effectively study wireless, 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 3D 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 was 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.

Ray tracing is a powerful tool that can be used to predict wireless channel characteristics, reducing the need for extensive channel measurements for channel characterization, evaluation of performance of sensing applications such as position location, and wireless network deployment. In this work, NYURay, a 3D mmWave and sub-THz ray tracer, is introduced, which is calibrated to wireless channel propagation measurements conducted at 28, 73, and 140 GHz, in indoor office, outdoor, and factory environments. We present an accurate yet low-complexity calibration procedure to obtain electrical properties of materials in any environment by modeling the reflection coefficient of building materials to be independent of the angle of incidence, a simplification shown to be quite effective in [1] over 30 years ago. We show that after calibration, NYURay can accurately predict individual directional multipath signal power. The standard deviation in the error of the directional multipath power predicted by the ray tracer compared to the directional measured power was less than 3 dB in indoor office environments and less than 2 dB in outdoor and factory environments.

This paper presents sub-Terahertz (THz) channel characterization and modeling for an indoor industrial scenario based on radio propagation measurements at 142 GHz in four factories. We selected 82 transmitter-receiver (TX-RX) locations in both line-of-sight (LOS) and non-LOS (NLOS) conditions and collected over 75,000 spatial and temporal channel impulse responses. The TX-RX distance ranged from 5 to 87 m. Steerable directional horn antennas were employed at both ends and were switched between vertical and horizontal polarization. Measurements were conducted with the low RX and high RX to characterize the propagation channel for close-to-floor applications such as automated guided vehicles. Results show that the low RXs experience an average path loss increase of 10.7 dB and 6.0 dB at LOS and NLOS locations, respectively. In addition, channel enhancement measurements were conducted using a steerable large flat metal plate as a passive reflecting surface, demonstrating omnidirectional path loss reduction from 0.5 to 22 dB with a mean of 6.5 dB. This paper presents the first statistical channel characterization and path loss modeling at sub-THz frequencies, highlighting the potential for ultra-broadband factory communications in the 6G era.

Future wireless cellular networks will utilize millimeter-wave and sub-THz frequencies and deploy small-cell base stations to achieve data rates on the order of hundreds of gigabits per second per user. The move to sub-THz frequencies will require attention to sustainability and reduction of power whenever possible to reduce the carbon footprint while maintaining adequate battery life for the massive number of resource-constrained devices to be deployed. This article analyzes power consumption of future wireless networks using a new metric, a figure of merit called the power waste factor ( W ), which shows promise for the study and development of “green G” - green technology for future wireless networks. Using W , power efficiency can be considered by quantifying the power wasted by all devices on a signal path in a cascade. We then show that the consumption efficiency factor (CEF), defined as the ratio of the maximum data rate achieved to the total power consumed, is a novel and powerful measure of power efficiency which shows that less energy per bit is expended as the cell size shrinks and carrier frequency and channel bandwidth increase. Our findings offer a standard approach to calculating and comparing power consumption and energy efficiency.

Future wireless cellular networks will utilize millimeter wave and sub-THz frequencies and deploy small-cell base stations to achieve data rates on the order of hundreds of Gigabits per second per user. The move to sub-THz frequencies will require attention to sustainability and reduction of power whenever possible to reduce the carbon footprint while maintaining adequate battery life for the massive number of resource-constrained devices to be deployed. This article analyzes power consumption of future wireless networks using a new metric, the power waste factor ( W ), which shows promise for the study and development of "green G" - green technology for future wireless networks. Using W , power efficiency can be considered by quantifying the power wasted by all devices on a signal path in a cascade. We then show that the consumption efficiency factor (CEF), defined as the ratio of the maximum data rate achieved to the total power consumed, is a novel and powerful measure of power efficiency that shows less energy per bit is expended as the cell size shrinks and carrier frequency and channel bandwidth increase. Our findings offer a standard approach to calculating and comparing power consumption and energy efficiency.