9 papers
FullPASS: Geometry Optimization for Full-Duplex Pinching-Antenna Systems
Morteza Barzegar Astanjin, Seyed Mohammad Azimi-Abarghouyi, Thomas Eriksson +1
This paper proposes FullPASS, an in-band full-duplex architecture for pinching-antenna systems (PASSs) based on two parallel waveguides. The FullPASS transceiver simultaneously com…
AirPASS: Over-the-Air Federated Learning via Pinching Antenna Systems
Seyed Mohammad Azimi-Abarghouyi, Christopher G. Brinton
This paper investigates over-the-air federated learning (AirFL) in wireless systems where the access point is equipped with a multi-waveguide pinching antenna system (PASS). We ado…
Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing
Seyed Mohammad Azimi-Abarghouyi, Carlo Fischione, Kaibin Huang
Over-the-Air Federated Learning (AirFL) is an emerging paradigm that tightly integrates wireless signal processing and distributed machine learning to enable scalable AI at the net…
Mitigating Heterogeneity-Induced Drift in Hierarchical Sign-Based Federated Learning
Amirreza Kazemi, Seyed Mohammad Azimi-Abarghouyi, Gabor Fodor +1
Hierarchical federated learning (HFL) is well suited for large-scale wireless and Internet of Things systems, where devices communicate with nearby edge servers before reaching the…
Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design
Seyed Mohammad Azimi-Abarghouyi, Mehdi Bennis, Leandros Tassiulas
Federated learning (FL) is fundamentally a distributed optimization problem executed by communicating agents with local data, local computation, and partial system visibility. Once…
Out-of-Air Computation: Enabling Structured Extraction from Wireless Superposition
Seyed Mohammad Azimi-Abarghouyi
Over-the-air computation (AirComp) has traditionally been built on the principle of pre-embedding computation into transmitted waveforms or on exploiting massive antenna arrays, of…