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1. Millimeter Wave Position Location using Multipath Differentiation for 3GPP using Field Measurements

   Ojas Kanhere, Theodore S. ( December 2020 , 2020 IEEE Global Communciations conference)

   null (Ed.)

   3GPP air interface standards support meter-level position location of a user in a cellular network. With wider bandwidths and narrow antenna beamwidths available at mmWave frequencies, cellular networks now have the potential to provide sub-meter position location for each user. In this work, we provide an overview of 3GPP position location techniques that are designed for line-of-sight propagation. We discuss additional measurements required in the 3GPP standard that enable multipath-based non-line-of-sight position location. Further, we validate the concepts in this paper by using field data to test a map-based position location algorithm in an indoor office environment which has dimensions of 35 m by 65.5 m. We demonstrate how the fusion of angle of arrival and time of flight information in concert with a 3-D map of the office provides a mean accuracy of 5.72 cm at 28 GHz and 6.29 cm at 140 GHz, over 23 receiver distances ranging from 4.2 m to 32.3 m, using a single base station in line-of-sight and non-line-of-sight. We also conduct a theoretical analysis of the typical error experienced in the map-based position location algorithm and show that the complexity of the map-based algorithm is low enough to allow real-time implementation. 

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2. Outdoor sub-THz Position Location and Tracking using Field Measurements at 142 GHz

   Kanhere, O ; Rappaport, T.S. ( June 2021 , 2021 IEEE International Conference on Communications (ICC), June 2021)

   AbstractÐFuture sub-THz cellular deployments may be utilized to complement the coverage of the global positioning system (GPS) and provide centimeter-level accuracy. In this work, we use measurement data at 142 GHz to test a map-based position location algorithm in an outdoor urban microcell (UMi) environment. We utilize an extended Kalman filter (EKF) to track the position of the user equipment (UE) along a rectangular track, with the transmitter-receiver separation distances varying from 24.3 m to 52.8 m. The position and velocity of the UE are tracked by the EKF, with measurements of the angle of arrival and time of flight information obtained along an outdoor track, to provide a mean accuracy of 24.8 cm at 142 GHz, over 34 UE locations, using a single base station in line-of-sight and non-line-of-sight. 

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3. Position Locationing for Millimeter Wave Systems

   https://doi.org/10.1109/GLOCOM.2018.8647983  

   Kanhere, Ojas ; Rappaport, Theodore S. ( December 2018 , 2018 IEEE Global Communications Conference (GLOBECOM))

   Abstract: The vast amount of spectrum available for millimeter wave (mmWave) wireless communication systems will support accurate real-time positioning concurrent with communication signaling. This paper demonstrates that accurate estimates of the position of an unknown node can be determined using estimates of time of arrival (ToA), angle of arrival (AoA), as well as data fusion or machine learning. Real-world data at 28 GHz and 73 GHz is used to show that AoA-based localization techniques will need to be augmented with other positioning techniques. The fusion of AoA-based positioning with received power measurements for RXs in an office which has dimensions of 35 m by 65.5 m is shown to provide location accuracies ranging from 16 cm to 3.25 m, indicating promise for accurate positioning capabilities in future networks. Received signal strength intensity (RSSI) based positioning techniques that exploit the ordering of the received power can be used to determine rough estimates of user position. Prediction of received signal characteristics is done using 2-D ray tracing. 

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4. Development of a Free-Flight Wind Test Facility Featuring a GNSS Simulator to Achieve Immersive Drone Testing

   https://doi.org/10.2514/6.2022-2052  

   Catry, Guillaume ; Thurling, Andy ; Bosson, Nicolas ; Dzodic, Aleksandar ; Le Porin, Peter ; Wang, Ningshan ; Sanyal, Amit K. ; Noca, Flavio ; Glauser, Mark N. ( January 2022 , AIAA SCITECH 2022 Forum)

   Weather, winds, thermals, and turbulence pose an ever-present challenge to small UAS. These challenges become magnified in rough terrain and especially within urban canyons. As the industry moves towards Beyond Visual Line of Sight (BVLOS) and fully autonomous operations, resilience to weather perturbations will be key. As the human decision-maker is removed from the in-situ environment, producing control systems that are robust will be paramount to the preservation of any Airspace System. Safety requirements and regulations require quantifiable performance metrics to guarantee a safe aerial environment with ever- increasing traffic. In this regards, the effect of wind and weather disturbances on a UAS and its ability to reject these disturbances present some unique concerns. Currently, drone manufacturers and operators rely on outdoor testing during windy days (or in windy locations) and onboard logging to evaluate and improve the flight worthiness, reliability and perturbation rejection capability of their vehicles. Waiting for the desired weather or travelling to a windier location is cost- and time-inefficient. Moreover, the conditions found on outdoor test sites are difficult to quantify and repeatability is non-existent. To address this situation, a novel testing methodology is proposed, combining artificial wind generation thanks to a multi-fan array wind generator (windshaper), coherent GNSS signal generation and accurate tracking of the test subject thanks to motion capture cameras. In this environment, the drone being tested can fly freely, follow missions and experience wind perturbations whilst staying in a modest indoor volume. By coordinating the windshaper, the motion tracking feedback and the position emulated by the GNSS signal generator with the drone’s mission profile, it was demonstrated that outdoor flight conditions can be reliably recreated in a controlled and repeatable environment. Specifically, thanks to real-time update of the position simulated by the GNSS signal generator, it was possible to demonstrate that the drone’s perception of the situation is similar to a corresponding mission being executed outdoor. In this work, the drone was subjected to three distinct flight cases: (1) hover in 2 m s−1 wind, (2) forward flight at 2 m s−1 without wind and (3) forward flight at 2 m s−1 with 2 m s−1 headwind. In each case, it could be demonstrated that by using indoor GNSS signal simulation and wind generation, the drone displays the characteristics of a 20 m move forward, while actually staying stationary in the test volume, within ±1 m. Further development of this methodology opens the door for fully integrated hardware-in- the-loop simulation of drone flight operations. 

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5. Millimeter Wave and Sub-THz Indoor Radio Propagation Channel Measurements, Models, and Comparisons in an Office Environment

   Yunchou Xing, Theodore S. ( October 2021 , IEEE communications letters)

   Abstract—This letter provides a comparison of indoor radio propagation measurements and corresponding channel statistics at 28, 73, and 140 GHz, based on extensive measurements from 2014-2020 in an indoor office environment. Side-by-side comparisons of propagation characteristics (e.g., large-scale path loss and multipath time dispersion) across a wide range of frequencies from the low millimeter wave band of 28 GHz to the sub-THz band of 140 GHz illustrate the key similarities and differences in indoor wireless channels. The measurements and models show remarkably similar path loss exponents over frequencies in both line-of-sight (LOS) and non-LOS (NLOS) scenarios, when using a one meter free space reference distance, while the multipath time dispersion becomes smaller at higher frequencies. The 3GPP indoor channel model overestimates the large-scale path loss and has unrealistic large numbers of clusters and multipath components per cluster compared to the measured channel statistics in this letter. Index Terms—mmWave, THz, channel models, multipath time dispersion, 5G, 6G, large-scale path loss, 3GPP InH. 

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