117 citations · 296 across the 11 of their papers we have counts for
11 papers
Sparse Incremental Aggregation in Satellite Federated Learning
Nasrin Razmi, Sourav Mukherjee, Bho Matthiesen +2
This paper studies Federated Learning (FL) in low Earth orbit (LEO) satellite constellations, where satellites are connected via intra-orbit inter-satellite links (ISLs) to their n…
Energy-Aware Federated Learning in Satellite Constellations
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
Federated learning in satellite constellations, where the satellites collaboratively train a machine learning model, is a promising technology towards enabling globally connected i…
Sparse Incremental Aggregation in Multi-Hop Federated Learning
Sourav Mukherjee, Nasrin Razmi, Armin Dekorsy +2
This paper investigates federated learning (FL) in a multi-hop communication setup, such as in constellations with inter-satellite links. In this setup, part of the FL clients are…
Scheduling for On-Board Federated Learning with Satellite Clusters
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
Mega-constellations of small satellites have evolved into a source of massive amount of valuable data. To manage this data efficiently, on-board federated learning (FL) enables sat…
On-board Federated Learning for Satellite Clusters with Inter-Satellite Links
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
The emergence of mega-constellations of interconnected satellites has a major impact on the integration of cellular wireless and non-terrestrial networks, while simultaneously offe…
Scheduling for Ground-Assisted Federated Learning in LEO Satellite Constellations
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
Distributed training of machine learning models directly on satellites in low Earth orbit (LEO) is considered. Based on a federated learning (FL) algorithm specifically targeted at…
Federated Learning in Satellite Constellations
Bho Matthiesen, Nasrin Razmi, Israel Leyva-Mayorga +2
Federated learning (FL) has recently emerged as a distributed machine learning paradigm for systems with limited and intermittent connectivity. This paper presents the new context…
On-Board Federated Learning for Dense LEO Constellations
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
Mega-constellations of small-size Low Earth Orbit (LEO) satellites are currently planned and deployed by various private and public entities. While global connectivity is the main…
Ground-Assisted Federated Learning in LEO Satellite Constellations
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy +1
In Low Earth Orbit (LEO) mega constellations, there are relevant use cases, such as inference based on satellite imaging, in which a large number of satellites collaboratively trai…
Analysis of D2D Communication with RF Energy Harvesting and Interference Management
Nasrin Razmi, Mehdi Mahdavi, Mohammadali Mohammadi +1
Device-to-device (D2D) underlaid cellular network, enabled with radio frequency energy harvesting (RFEH), and enhanced interference management schemes is a promising candidate to i…
Analysis of LoRaWAN Uplink with Multiple Demodulating Paths and Capture Effect
René Brandborg Sørensen, Nasrin Razmi, Jimmy Jessen Nielsen +1
Low power wide area networks (LPWANs), such as the ones based on the LoRaWAN protocol, are seen as enablers of large number of IoT applications and services. In this work, we asses…