output
20182025
most citedDeep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing

111 citations

6 papers

eess.SP2025★ 1 cited

The Expected Peak-to-Average Power Ratio of White Gaussian Noise in Sampled I/Q Data

Adam Wunderlich, Aric Sanders

One of the fundamental endeavors in radio frequency (RF) metrology is to measure the power of signals, where a common aim is to estimate the peak-to-average power ratio (PAPR), whi…

eess.SP2022★ 5 cited

Data-Driven Modeling of Noise Time Series with Convolutional Generative Adversarial Networks

Adam Wunderlich, Jack Sklar

Random noise arising from physical processes is an inherent characteristic of measurements and a limiting factor for most signal processing and data analysis tasks. Given the recen…

cs.IT2021

A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

Akbar Sayeed, Peter Vouras, Camillo Gentile +13

A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by sounders at millimeter-wave (…

eess.SP2021★ 3 cited

Multi-Criteria Radio Spectrum Sharing With Subspace-Based Pareto Tracing

Zachary Grey, Susanna Mosleh, Jacob Rezac +3

Radio spectrum is a high-demand finite resource. To meet growing demands of data throughput for forthcoming and deployed wireless networks, new wireless technologies must operate i…

cs.IT2020★ 8 cited

On the Outage Performance of SWIPT-NOMA-CRS with imperfect SIC and CSI

Ferdi Kara

In this paper, a non-orthogonal multiple access based cooperative relaying system (NOMA-CRS) is considered to increase spectral efficiency. Besides, the simultaneous wireless infor…

eess.SP2018★ 111 cited

Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing

W. Max Lees, Adam Wunderlich, Peter Jeavons +2

In the United States, the Federal Communications Commission has adopted rules permitting commercial wireless networks to share spectrum with federal incumbents in the 3.5~GHz Citiz…