1 citations · 2 across the 22 of their papers we have counts for
6 papers · 1 filter
Learning OTA: A Unified Framework for Edge Sensing, Computation, and Communication
Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton
Most federated learning (FL) studies implicitly assume that training data is readily available at participating edge devices. In practice, this data must first be acquired through…
Distributed Edge Learning under Imperfect Data Sensing
Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton
Distributed learning systems typically assume that local data is already available at clients with fixed quality, while in practice, data is sensed through imperfect physical proce…
AISAC: Closing the Loop Between AI and Integrated Sensing and Communication for 6G
Mehdi Karbalayghareh, Abhishek Rajasekaran, Xiaoyan Ma +2
Integrated sensing and communication (ISAC) and AI-and-communication (AIAC) are identified as separate usage scenarios in the ITU IMT-2030 vision for sixth-generation (6G) networks…
Coherence-Aware Over-the-Air Distributed Learning under Heterogeneous Link Impairments
Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton
Distributed machine learning (ML) over wireless networks hinges on accurate channel state information (CSI) and efficient exchange of high-dimensional model updates. These demands…
Coherence-Aware Distributed Learning under Heterogeneous Downlink Impairments
Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton
The performance of federated learning (FL) over wireless networks critically depends on accurate and timely channel state information (CSI) across distributed devices. This require…
Coding for Gaussian Two-Way Channels: Linear and Learning-Based Approaches
Junghoon Kim, Taejoon Kim, Anindya Bijoy Das +3
Although user cooperation cannot improve the capacity of Gaussian two-way channels (GTWCs) with independent noises, it can improve communication reliability. In this work, we aim t…