1.6k citations · 1.6k across the 7 of their papers we have counts for
8 papers
Transformer-Driven Neural Beamforming with Imperfect CSI in Urban Macro Wireless Channels
Cemil Vahapoglu, Timothy J. O'Shea, Wan Liu +2
The literature is abundant with methodologies focusing on using transformer architectures due to their prominence in wireless signal processing and their capability to capture long…
Deep Learning Based Joint Multi-User MISO Power Allocation and Beamforming Design
Cemil Vahapoglu, Timothy J. O'Shea, Tamoghna Roy +1
The evolution of fifth generation (5G) wireless communication networks has led to an increased need for wireless resource management solutions that provide higher data rates, wide…
Deep Learning Based Uplink Multi-User SIMO Beamforming Design
Cemil Vahapoglu, Timothy J. O'Shea, Tamoghna Roy +1
The advancement of fifth generation (5G) wireless communication networks has created a greater demand for wireless resource management solutions that offer high data rates, extensi…
Wideband Signal Localization with Spectral Segmentation
Nathan West, Tamoghna Roy, Timothy O'Shea
Signal localization is a spectrum sensing problem that jointly detects the presence of a signal and estimates a center frequency and bandwidth. This is a step beyond most spectrum…
A Wideband Signal Recognition Dataset
Nathan West, Timothy O'Shea, Tamoghna Roy
Signal recognition is a spectrum sensing problem that jointly requires detection, localization in time and frequency, and classification. This is a step beyond most spectrum sensin…
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
Timothy J. O'Shea, Tamoghna Roy, Nathan West
Channel modeling is a critical topic when considering designing, learning, or evaluating the performance of any communications system. Most prior work in designing or learning new…
Physical Layer Communications System Design Over-the-Air Using Adversarial Networks
Timothy J. O'Shea, Tamoghna Roy, Nathan West +1
This paper presents a novel method for synthesizing new physical layer modulation and coding schemes for communications systems using a learning-based approach which does not requi…
Over the Air Deep Learning Based Radio Signal Classification
Timothy J. O'Shea, Tamoghna Roy, T. Charles Clancy
We conduct an in depth study on the performance of deep learning based radio signal classification for radio communications signals. We consider a rigorous baseline method using hi…