11 papers
Outage Analysis and Bilevel Resource Optimization in RIS-Assisted Clustered UAV-NOMA Networks
Masoud Ghazikor, Ly V. Nguyen, Morteza Hashemi
This paper investigates RIS-assisted downlink UAV communications based on NOMA. Since conventional NOMA becomes difficult to scale as the number of UAVs grows, we develop a cluster…
Partially-Observable Transmission Control for UAV-Enabled Federated Learning in IoT Networks
Masoud Ghazikor, Zhou Ni, Morteza Hashemi
Uncrewed aerial vehicle (UAV)-enabled federated learning (FL) can provide flexible, on-demand edge intelligence for large-scale IoT deployments, but operating in shared unlicensed…
A Vertical Look at UAV Connectivity in the Wild: Cellular vs. Starlink, 3D Characterization, and Performance Prediction
Sravan Reddy Chintareddy, Sherwan Jalal Abdullah, Justin D. Clough +3
In this paper, we present an open-source measurement platform designed to characterize the performance of commercial cellular (Verizon, a major US provider) and LEO satellite (Star…
Personalized Federated Learning-Driven Beamforming Optimization for Integrated Sensing and Communication Systems
Zhou Ni, Sravan Reddy Chintareddy, Peiyuan Guan +1
In this paper, we propose an Expectation-Maximization-based (EM) Personalized Federated Learning (PFL) framework for multi-objective optimization (MOO) in Integrated Sensing and Co…
Performance Analysis of RIS-Assisted UAV Communication in NOMA Networks
Masoud Ghazikor, Van Ly Nguyen, Morteza Hashemi
This paper investigates the performance of downlink non-orthogonal multiple access (NOMA) communication in unmanned aerial vehicle (UAV) networks enhanced by partitionable reconfig…
A Versatile and Programmable UAV Platform for Radio Access Network and End-to-End Cellular Measurements
Sherwan Jalal Abdullah, Sravan Reddy Chintareddy, Victor S. Frost +2
In this work, we develop a measurement platform to capture mobile network performance metrics including coverage and quality of service in regions where conventional coverage testi…
pFedWN: A Personalized Federated Learning Framework for D2D Wireless Networks with Heterogeneous Data
Zhou Ni, Masoud Ghazikor, Morteza Hashemi
Traditional Federated Learning (FL) approaches often struggle with data heterogeneity across clients, leading to suboptimal model performance for individual clients. To address thi…
Optimizing NOMA Transmissions to Advance Federated Learning in Vehicular Networks
Ziru Chen, Zhou Ni, Peiyuan Guan +4
Diverse critical data, such as location information and driving patterns, can be collected by IoT devices in vehicular networks to improve driving experiences and road safety. Howe…
Channel-Aware Distributed Transmission Control and Video Streaming in UAV Networks
Masoud Ghazikor, Keenan Roach, Kenny Cheung +1
In this paper, we study the problem of distributed transmission control and video streaming optimization for UAVs operating in unlicensed spectrum bands. We develop a rigorous cros…
Federated Learning-based Collaborative Wideband Spectrum Sensing and Scheduling for UAVs in UTM Systems
Sravan Reddy Chintareddy, Keenan Roach, Kenny Cheung +1
In this paper, we propose a data-driven framework for collaborative wideband spectrum sensing and scheduling for networked unmanned aerial vehicles (UAVs), which act as the seconda…
Interference-Aware Queuing Analysis for Distributed Transmission Control in UAV Networks
Masoud Ghazikor, Keenan Roach, Kenny Cheung +1
In this paper, we investigate the problem of distributed transmission control for unmanned aerial vehicles (UAVs) operating in unlicensed spectrum bands. We develop a rigorous inte…