3 citations · 6 across the 14 of their papers we have counts for
14 papers
A Traffic-Aware QoS-Energy Consumption Tradeoff Study for Integrated 6G TN & NTNs
Azim Akhtarshenas, Henri Alam, Henri Alam† +2
Motivated by the Hypercell concept, we extend BLASTER to investigate the trade-off between network quality of service (QoS) and terrestrial energy consumption in integrated terrest…
Low-Altitude Platform Stations for Dense Urban Connectivity
German Svistunov, Azim Akhtarshenas, Matteo Bernabè +1
This paper evaluates the downlink performance of 5G non-terrestrial networks (NTNs) realized via low-altitude platform station (LAPS)-mounted base stations, and compares it against…
Passive AoA Estimation of COTS 5G NR Handsets from Uplink SRS: A Practical USRP-B210 Implementation
Ricardo N. Barrios-Muñoz, Azim Akhtarshenas, David Gomez-Barquero +1
This paper presents a passive network-side framework for estimating the uplink angle of arrival (AoA) of unmodified commercial 5G handsets from native Sounding Reference Signal (SR…
Indirect Estimation of SINR via SSB and CSI-RS RSRP in 5G NR
Leonardo Spampinato, Mahamadou Togola, Matteo Bernabè +3
Predicting user equipment (UE) performance is essential for proactive network control, resource management, and digital twin sandboxes. However, the inherent flexibility and comple…
Centralized PPO-Based DRL for Multi-UAV-BS Positioning and Trajectory Optimization in Disaster Response Networks
Azim Akhtarshenas, Mario Rico Ibanez, Matteo Bernabe +2
Unmanned aerial vehicle-mounted base stations (UAV-BSs) constitute a flexible and effective solution for global positioning system (GPS)-free emergency and disaster scenarios, wher…
Wind-Resilient Trajectory Optimization for UAV-BS Networks: TD3 for Continuous Service Availability
Azim Akhtarshenas, German Svistunov, Kuangyu Zheng +1
Unmanned aerial vehicle (UAV)-mounted base stations are highly susceptible to wind disturbances such as gusts and turbulence, which induce positional drift and degrade communicatio…
PPO-Based Dynamic Positioning of HAPS-BS in Wind-Disturbed Stratospheric Maritime Networks
Azim Akhtarshenas, German Svistunov, Matteo Bernabè +2
High-Altitude Platform Stations (HAPS) offer a promising solution for wide-area wireless coverage in maritime regions lacking terrestrial infrastructure. However, maintaining relia…
Bridging Earth and Space: A Survey on HAPS for Non-Terrestrial Networks
G. Svistunov, A. Akhtarshenas, D. López-Pérez +3
HAPS are emerging as key enablers in the evolution of 6G wireless networks, bridging terrestrial and non-terrestrial infrastructures. Operating in the stratosphere, HAPS can provid…
Efficient Malicious UAV Detection Using Autoencoder-TSMamba Integration
Azim Akhtarshenas, Ramin Toosi, David López-Pérez +2
Malicious Unmanned Aerial Vehicles (UAVs) present a significant threat to next-generation networks (NGNs), posing risks such as unauthorized surveillance, data theft, and the deliv…
Optimizing UAV Aerial Base Station Flights Using DRL-based Proximal Policy Optimization
Mario Rico Ibanez, Azim Akhtarshenas, David Lopez-Perez +1
Unmanned aerial vehicle (UAV)-based base stations offer a promising solution in emergencies where the rapid deployment of cutting-edge networks is crucial for maximizing life-savin…
ChatGPT or A Silent Everywhere Helper: A Survey of Large Language Models
Azim Akhtarshenas, Afshin Dini, Navid Ayoobi
Large Language Models (LLMs) have revo lutionized natural language processing Natural Language Processing (NLP), with Chat Generative Pre-trained Transformer (ChatGPT) standing out…
CNN Autoencoder Resizer: A Power-Efficient LoS/NLoS Detector in MIMO-enabled UAV Networks
Azim Akhtarshenas, Navid Ayoobi, David Lopez-Perez +2
Optimizing the design, performance, and resource efficiency of wireless networks (WNs) necessitates the ability to discern Line of Sight (LoS) and Non-Line of Sight (NLoS) scenario…
Shapley-Based Data Valuation with Mutual Information: A Key to Modified K-Nearest Neighbors
Mohammad Ali Vahedifar, Azim Akhtarshenas, Mohammad Mohammadi Rafatpanah +1
The K-Nearest Neighbors (KNN) algorithm is widely used for classification and regression; however, it suffers from limitations, including the equal treatment of all samples. We pro…
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
Azim Akhtarshenas, Mohammad Ali Vahedifar, Navid Ayoobi +4
Robust machine learning (ML) models can be developed by leveraging large volumes of data and distributing the computational tasks across numerous devices or servers. Federated lear…