10 citations · 12 across the 27 of their papers we have counts for
31 papers
Pilot-Projected Nonlinear Self-Interference Estimation with Simultaneous Uplink Training
Seyed Mohammad Azimi-Abarghouyi, Thomas Eriksson
This paper considers nonlinear digital self-interference (SI) cancellation and uplink-channel estimation for single-antenna in-band full-duplex radios when a desired uplink pilot i…
Progressive-Resolution Secure Aggregation for Federated Learning
Seyed Mohammad Azimi-Abarghouyi
Secure aggregation lets a server recover an aggregate of client updates without observing any individual update, but conventional protocols fix the aggregate precision when clients…
FedHV: Low-Overhead Hypervolume Weighting for Federated Multi-Objective Optimization
Amirardalan Dehghanpour, Seyed Mohammad Azimi-Abarghouyi, Christopher G. Brinton
Task-wise federated multi-objective optimization (FedMOO) trains a shared model for competing prediction objectives under heterogeneous data, partial participation, and communicati…
Occupancy-Domain Over-the-Air Computation
Seyed Mohammad Azimi-Abarghouyi
Over-the-air computation (AirComp) aggregates distributed data through the wireless multiple-access channel, but coherent implementations require channel state information (CSI), p…
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…
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 Function Extraction from Wireless Superposition
Seyed Mohammad Azimi-Abarghouyi
Over-the-air computation (AirComp) broadly exploits the superposition property of wireless multiple-access channels (MACs) to compute functions of distributed data. Within this bro…
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…
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…
A Generalized Hierarchical Federated Learning Framework with Theoretical Guarantees
Seyed Mohammad Azimi-Abarghouyi, Carlo Fischione
Almost all existing hierarchical federated learning (FL) models are limited to two aggregation layers, restricting scalability and flexibility in complex, large-scale networks. In…
Hierarchical Federated ADMM
Seyed Mohammad Azimi-Abarghouyi, Nicola Bastianello, Karl H. Johansson +1
In this paper, we depart from the widely-used gradient descent-based hierarchical federated learning (FL) algorithms to develop a novel hierarchical FL framework based on the alter…
Over-the-Air Federated Learning via Weighted Aggregation
Seyed Mohammad Azimi-Abarghouyi, Leandros Tassiulas
This paper introduces a new federated learning scheme that leverages over-the-air computation. A novel feature of this scheme is the proposal to employ adaptive weights during aggr…
Compute-Update Federated Learning: A Lattice Coding Approach Over-the-Air
Seyed Mohammad Azimi-Abarghouyi, Lav R. Varshney
This paper introduces a federated learning framework that enables over-the-air computation via digital communications, using a new joint source-channel coding scheme. Without relyi…
A Hierarchical Federated Learning Approach for the Internet of Things
Seyed Mohammad Azimi-Abarghouyi, Viktoria Fodor
This paper presents a novel federated learning solution, QHetFed, suitable for large-scale Internet of Things deployments, addressing the challenges of large geographic span, commu…
Federated Learning via Lattice Joint Source-Channel Coding
Seyed Mohammad Azimi-Abarghouyi, Lav R. Varshney
This paper introduces a universal federated learning framework that enables over-the-air computation via digital communications, using a new joint source-channel coding scheme. Wit…
Hierarchical Over-the-Air Federated Learning with Awareness of Interference and Data Heterogeneity
Seyed Mohammad Azimi-Abarghouyi, Viktoria Fodor
When implementing hierarchical federated learning over wireless networks, scalability assurance and the ability to handle both interference and device data heterogeneity are crucia…
A Tractable Probability Distribution with Applications in Three-Dimensional Statistics
Seyed Mohammad Azimi-Abarghouyi
This paper introduces and characterizes a new family of continuous probability distributions applicable to norm distributions in three-dimensional random spaces, specifically for t…
Scalable Hierarchical Over-the-Air Federated Learning
Seyed Mohammad Azimi-Abarghouyi, Viktoria Fodor
When implementing hierarchical federated learning over wireless networks, scalability assurance and the ability to handle both interference and device data heterogeneity are crucia…
Matern Cluster Process with Holes at the Cluster Centers
Seyed Mohammad Azimi-Abarghouyi, Harpreet S. Dhillon
Inspired by recent applications of point processes to biological nanonetworks, this paper presents a novel variant of a Matérn cluster process (MCP) in which the points located wit…
Fundamentals of Clustered Molecular Nanonetworks
Seyed Mohammad Azimi-Abarghouyi, Harpreet S. Dhillon, Leandros Tassiulas
We present a comprehensive approach to the modeling, performance analysis, and design of clustered molecular nanonetworks in which nano-machines of different clusters release an ap…
Stochastic Design and Analysis of Wireless Cloud Caching Networks
Seyed Mohammad Azimi-Abarghouyi, Masoumeh Nasiri-Kenari, Merouane Debbah
This paper develops a stochastic geometry-based approach for the modeling, analysis, and optimization of wireless cloud caching networks comprised of multiple-antenna radio units (…
Outage Probability Analysis of Uplink NOMA over Ultra-High-Speed FSO-Backhauled Systems
Mohammad Vahid Jamali, Seyed Mohammad Azimi-Abarghouyi, Hessam Mahdavifar
In this paper, we consider a relay-assisted uplink non-orthogonal multiple access (NOMA) system where two radio frequency (RF) users are grouped for simultaneous transmission, over…
Stochastic Geometry Modeling and Analysis of Finite Millimeter Wave Wireless Networks
Seyed Mohammad Azimi-Abarghouyi, Behrooz Makki, Masoumeh Nasiri-Kenari +1
This paper develops a stochastic geometry-based approach for the modeling and analysis of finite millimeter wave (mmWave) wireless networks where a random number of transmitters an…