141 citations · 290 across the 58 of their papers we have counts for
8 papers · 1 filter
Characterizing the First-Arriving Multipath Component in 5G Millimeter Wave Networks: TOA, AOA, and Non-Line-of-Sight Bias
Christopher E. O'Lone, Harpreet S. Dhillon, R. Michael Buehrer
This paper presents a stochastic geometry-based analysis of propagation statistics for 5G millimeter wave (mm-wave) cellular. In particular, the time-of-arrival (TOA) and angle-of-…
Constrained Online Learning to Mitigate Distortion Effects in Pulse-Agile Cognitive Radar
Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone
Pulse-agile radar systems have demonstrated favorable performance in dynamic electromagnetic scenarios. However, the use of non-identical waveforms within a radar's coherent proces…
The RFML Ecosystem: A Look at the Unique Challenges of Applying Deep Learning to Radio Frequency Applications
Lauren J. Wong, William H. Clark, Bryse Flowers +3
While deep machine learning technologies are now pervasive in state-of-the-art image recognition and natural language processing applications, only in recent years have these techn…
Efficient Online Learning for Cognitive Radar-Cellular Coexistence via Contextual Thompson Sampling
Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone
This paper describes a sequential, or online, learning scheme for adaptive radar transmissions that facilitate spectrum sharing with a non-cooperative cellular network. First, the…
Predicting Bit Error Rate from Meta Information using Random Forests
Jianyuan Yu, Yue Xu, Hussein Metwaly Saad +1
With the increasing power of machine learning-based reasoning, the use of meta-information (e.g., digital signal modulation parameters, channel conditions, etc.) to predict the per…
Deep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments
Charles E. Thornton, Mark A. Kozy, R. Michael Buehrer +2
In this paper, dynamic non-cooperative coexistence between a cognitive pulsed radar and a nearby communications system is addressed by applying nonlinear value function approximati…
Interference Classification Using Deep Neural Networks
Jianyuan Yu, Mohammad Alhassoun, R. Michael Buehrer
The recent success in implementing supervised learning to classify modulation types suggests that other problems akin to modulation classification would eventually benefit from tha…
Experimental Analysis of Reinforcement Learning Techniques for Spectrum Sharing Radar
Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone +1
In this work, we first describe a framework for the application of Reinforcement Learning (RL) control to a radar system that operates in a congested spectral setting. We then comp…