FLSTRA: Federated Learning in Stratosphere

no code implementations • 1 Feb 2023 • Amin Farajzadeh, Animesh Yadav, Omid Abbasi, Wael Jaafar, Halim Yanikomeroglu

We propose a federated learning (FL) in stratosphere (FLSTRA) system, where a high altitude platform station (HAPS) facilitates a large number of terrestrial clients to collaboratively learn a global model without sharing the training data.

Federated Learning

VHetNets for AI and AI for VHetNets: An Anomaly Detection Case Study for Ubiquitous IoT

no code implementations • 14 Oct 2022 • Weili Wang, Omid Abbasi, Halim Yanikomeroglu, Chengchao Liang, Lun Tang, Qianbin Chen

In this article, we develop an AI-native VHetNets-enabled framework to provide the anomaly detection service for ubiquitous IoT, whose implementation is assisted by intelligent network management functionalities.

Anomaly Detection Intrusion Detection +1

Handling Interference in Integrated HAPS-Terrestrial Networks through Radio Resource Management

no code implementations • 15 Aug 2022 • Afsoon Alidadi Shamsabadi, Animesh Yadav, Omid Abbasi, Halim Yanikomeroglu

However, the problem of interference is the bottleneck for the optimal operation of such an integrated network.

Fairness Management

Caching and Computation Offloading in High Altitude Platform Station (HAPS) Assisted Intelligent Transportation Systems

no code implementations • 28 Jun 2021 • Qiqi Ren, Omid Abbasi, Gunes Karabulut Kurt, Halim Yanikomeroglu, Jian Chen

In addition, the caching technique is introduced for network edges to store some of the fundamental data from the HAPS so that large propagation delays can be reduced.

Edge-computing