Search Results for author: James V. Krogmeier

Found 9 papers, 2 papers with code

Simulation-Enhanced Data Augmentation for Machine Learning Pathloss Prediction

no code implementations3 Feb 2024 Ahmed P. Mohamed, Byunghyun Lee, Yaguang Zhang, Max Hollingsworth, C. Robert Anderson, James V. Krogmeier, David J. Love

To alleviate these challenges, this paper introduces a novel simulation-enhanced data augmentation method for ML pathloss prediction.

Data Augmentation

Constant Modulus Waveform Design with Block-Level Interference Exploitation for DFRC Systems

no code implementations16 Oct 2023 Byunghyun Lee, Anindya Bijoy Das, David J. Love, Christopher G. Brinton, James V. Krogmeier

Dual-functional radar-communication (DFRC) is a promising technology where radar and communication functions operate on the same spectrum and hardware.

Dynamic and Robust Sensor Selection Strategies for Wireless Positioning with TOA/RSS Measurement

no code implementations30 Apr 2023 Myeung Suk Oh, Seyyedali Hosseinalipour, Taejoon Kim, David J. Love, James V. Krogmeier, Christopher G. Brinton

For dynamic sensor selection, two greedy selection strategies are proposed, each of which exploits properties revealed in the derived CRLB expressions.

Propagation Measurements and Analyses at 28 GHz via an Autonomous Beam-Steering Platform

1 code implementation16 Feb 2023 Bharath Keshavamurthy, Yaguang Zhang, Christopher R. Anderson, Nicolo Michelusi, James V. Krogmeier, David J. Love

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.

Data-Driven Web-Based Patching Management Tool Using Multi-Sensor Pavement Structure Measurements

no code implementations10 Feb 2023 Sneha Jha, Yaguang Zhang, Bongsuk Park, Seonghwan Cho, James V. Krogmeier, Tandra Bagchi, John E. Haddock

Automating pavement maintenance suggestions is challenging, especially for actionable recommendations such as patching location, depth and priority. It is common practice among State agencies to manually inspect road segments of interest and decide maintenance requirements based on the pavement condition index (PCI). However, standalone PCI only evaluates the pavement surface condition and coupled with the variability in human perception of pavement distress, limits the accuracy and quality of current pavement maintenance practices. Here, a need for multi-sensor data integrated with standardized pavement distress condition ratings is required. This study explores the possibility of estimating the appropriate pavement patching strategy (i. e., patching location, depth, and quantity) by integrating pavement structural and surface condition assessment with pavement specific ratings of distress. Especially, it combines pavement structural condition assessment parameter;falling weight deflectometer deflections along with surface condition assessment parameters;international roughness index, and cracking density for a better representation of overall pavement distress condition. Then, a pavement specific threshold-based patching suggestion algorithm is implemented to evaluate the pavement overall distress condition into a priority-based patching suggestion. The novelty in the use of pavement specific thresholds is placed on its data-driven ability to determine threshold values from current road condition measurements using a reliability concept validated by the theoretical pavement condition rating, pavement structural number. A web-based patching manager tool (PMT) was implemented to automate the patching suggestion procedure and visualize the results. Validated with road surface images obtained from three-dimensional laser sensors, PMT could successfully capture localized distresses in existing pavements.

Management

Compressed Training for Dual-Wideband Time-Varying Sub-Terahertz Massive MIMO

no code implementations4 Jan 2022 Tzu-Hsuan Chou, Nicolo Michelusi, David J. Love, James V. Krogmeier

6G operators may use millimeter wave (mmWave) and sub-terahertz (sub-THz) bands to meet the ever-increasing demand for wireless access.

A Robotic Antenna Alignment and Tracking System for Millimeter Wave Propagation Modeling

1 code implementation14 Oct 2021 Bharath Keshavamurthy, Yaguang Zhang, Christopher R. Anderson, Nicolo Michelusi, James V. Krogmeier, David J. Love

In this paper, we discuss the design of a sliding-correlator channel sounder for 28 GHz propagation modeling on the NSF POWDER testbed in Salt Lake City, UT.

Fast Position-Aided MIMO Beam Training via Noisy Tensor Completion

no code implementations5 Aug 2020 Tzu-Hsuan Chou, Nicolo Michelusi, David J. Love, James V. Krogmeier

A data tensor is constructed by collecting beam-training measurements on a subset of positions and beams, and a hybrid noisy tensor completion (HNTC) algorithm is proposed to predict the received power across the coverage area, which exploits both the spatial smoothness and the low-rank property of MIMO channels.

Position

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