activity
20112026
most citedDeep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments

141 citations · 290 across the 58 of their papers we have counts for

collaborators
Showing 2021 · eess.SPShow all

6 papers · 2 filters

eess.SP2021★ 3 cited

Differential Modulation in Massive MIMO With Low-Resolution ADCs

Don-Roberts Emenonye, Carl Dietrich, R. Michael Buehrer

In this paper, we present a differential modulation and detection scheme for use in the uplink of a system with a large number of antennas at the base station, each equipped with l…

eess.SP2021

Differential Deep Detection in Massive MIMO With One-Bit ADC

Don-Roberts Emenonye, Carl Dietrich, R. Michael Buehrer

This article presents a differential detection scheme for the uplink of a massive MIMO system that employs one-bit quantizers on each receive antenna. We focus on the detection of…

eess.SP2021

Adversarial Multi-Player Bandits for Cognitive Radar Networks

William W. Howard, R. M. Buehrer, Anthony Martone

We model a radar network as an adversarial bandit problem, where the environment pre-selects reward sequences for each of several actions available to the network. This excludes en…

eess.SP2021★ 4 cited

Classification of Common Waveforms Including a Watchdog for Unknown Signals

C. Tanner Fredieu, Justin Bui, Anthony Martone +3

In this paper, we examine the use of a deep multi-layer perceptron model architecture to classify received signal samples as coming from one of four common waveforms, Single Carrie…

eess.SP2021

Open Set Wireless Standard Classification Using Convolutional Neural Networks

Samuel R. Shebert, Anthony F. Martone, R. Michael Buehrer

In congested electromagnetic environments, cognitive radios require knowledge about other emitters in order to optimize their dynamic spectrum access strategy. Deep learning classi…

eess.SP2021

Multi-Target Localization Using Polarization Sensitive Arrays

William W. Howard, R. Michael Buehrer

In this work we develop clustering techniques for the Bearing Only Target Localization (BOTL) problem. Our scenario has a receiver move along some path, generating bearing estimate…