141 citations · 148 across the 4 of their papers we have counts for
6 papers
Deep Learning Based MIMO Communications
Timothy J. O'Shea, Tugba Erpek, T. Charles Clancy
We introduce a novel physical layer scheme for single user Multiple-Input Multiple-Output (MIMO) communications based on unsupervised deep learning using an autoencoder. This metho…
Learning Approximate Neural Estimators for Wireless Channel State Information
Timothy J. O'Shea, Kiran Karra, T. Charles Clancy
Estimation is a critical component of synchronization in wireless and signal processing systems. There is a rich body of work on estimator derivation, optimization, and statistical…
Deep Reinforcement Learning Radio Control and Signal Detection with KeRLym, a Gym RL Agent
Timothy J. O'Shea, T. Charles Clancy
This paper presents research in progress investigating the viability and adaptation of reinforcement learning using deep neural network based function approximation for the task of…
Unsupervised Representation Learning of Structured Radio Communication Signals
Timothy J. O'Shea, Johnathan Corgan, T. Charles Clancy
We explore unsupervised representation learning of radio communication signals in raw sampled time series representation. We demonstrate that we can learn modulation basis function…
Radar Precoder Design for Spectral Coexistence with Coordinated Multi-point (CoMP) System
Jasmin A. Mahal, Awais Khawar, Ahmed Abdelhadi +1
This paper details the design of precoders for a MIMO radar spectrally coexistent with a MIMO cellular network. We focus on a coordinated multi-point (CoMP) system where a cluster…
Robust Resource Allocation with Joint Carrier Aggregation for Multi-Carrier Cellular Networks
Haya Shajaiah, Ahmed Abdelhadi, T. Charles Clancy
In this paper, we present a novel approach for robust optimal resource allocation with joint carrier aggregation to allocate multiple carriers resources optimally among users with…