21 citations · 52 across the 10 of their papers we have counts for
13 papers
Neural Network-based OFDM Receiver for Resource Constrained IoT Devices
Nasim Soltani, Hai Cheng, Mauro Belgiovine +10
Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are used for communication links in many current and emerging Internet of Things (IoT) applications, including the…
Going Beyond RF: How AI-enabled Multimodal Beamforming will Shape the NextG Standard
Debashri Roy, Batool Salehi, Stella Banou +7
Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G wireless standard promises autonomous network behavior and ultra-low-latency reconfiguratio…
AirNN: Neural Networks with Over-the-Air Convolution via Reconfigurable Intelligent Surfaces
Sara Garcia Sanchez, Guillem Reus Muns, Carlos Bocanegra +6
Over-the-air analog computation allows offloading computation to the wireless environment through carefully constructed transmitted signals. In this paper, we design and implement…
Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network
Batool Salehi, Guillem Reus-Muns, Debashri Roy +5
Beam selection for millimeter-wave links in a vehicular scenario is a challenging problem, as an exhaustive search among all candidate beam pairs cannot be assuredly completed with…
Machine Learning on Camera Images for Fast mmWave Beamforming
Batool Salehi, Mauro Belgiovine, Sara Garcia Sanchez +3
Perfect alignment in chosen beam sectors at both transmit- and receive-nodes is required for beamforming in mmWave bands. Current 802.11ad WiFi and emerging 5G cellular standards s…
Open-World Class Discovery with Kernel Networks
Zifeng Wang, Batool Salehi, Andrey Gritsenko +3
We study an Open-World Class Discovery problem in which, given labeled training samples from old classes, we need to discover new classes from unlabeled test samples. There are two…