This paper investigates the downlink performance of CoMS-NOMA networks from a system-level perspective.

The paper proposes AgentxGCore, an Agentic AI-Native layer that extends the 3GPP core network to enable self-organizing, self-adapting, and continuously optimized network management for 6G.

This paper presents a comprehensive survey on reconfigurable antennas for next-generation mobile networks, focusing on their potential and applications.

The paper proposes DRIFT, a lightweight joint channel estimation and prediction framework, to significantly reduce pilot overhead and boost spectral efficiency in power-constrained LEO Non-Terrestrial…

This paper analyzes the security vulnerabilities of emerging pay-for-use Wi-Fi hotspots in rural areas, demonstrating practical attacks like connection hijacking and rogue hotspots.

The paper investigates undetectable command and control (C2) channels within 5G core networks, demonstrating how compromised components can enable sophisticated attacks against subscriber security and…

The paper addresses the lack of independent measurement tools for modern mobile communication by designing and implementing open-source platforms to study cellular radio networks, operator services, a…

The paper proposes a communication-centric 6G-LLM architecture for tactical autonomous defense vehicles, demonstrating significant improvements in coordination and communication efficiency over conven…

The paper proposes a Digital Twin-assisted Adaptive Multi-Agent Deep Reinforcement Learning framework to intelligently manage spectrum and resources in complex, dynamic Open-RAN 6G networks utilizing…

The paper proposes StormShield, a fingerprint-based detection and mitigation technique implemented as an xApp on an O-RAN RIC, which effectively prevents gNB resource exhaustion caused by RRC signalin…

The paper proposes a channel prediction-based Physical Layer Authentication (PLA) framework using a Transformer module to maintain robust authentication accuracy against consecutive spoofing attacks i…

The paper introduces Devilray, a comprehensive adversarial model that systematically tests the realistic operational space of fake base stations, revealing significant blind spots in existing detectio…

The paper proposes RA-LWLM, a retrieval-augmented in-context localization framework that enables training-free, cross-scene wireless localization by externalizing scene-specific data into a fingerprin…

This paper provides a comprehensive review of the security vulnerabilities and privacy challenges inherent in the Open Radio Access Network (O-RAN) architecture for the 6G era, systematically categori…

This paper experimentally demonstrates the high detection performance of machine learning-based intrusion detection systems for identifying cyberattacks targeting OPC UA applications running over priv…

The paper proposes a resource-aware integer linear programming model to optimally allocate monitoring depth across heterogeneous network devices, balancing detection capability against computational a…

The paper proposes GUIDE, a physics-guided deep unfolding framework that enables practical, real-time cross-band channel prediction for AI-RAN by embedding wireless channel physics, significantly impr…

The paper proposes a standardized, zonal architecture and an open-source prototype for a dedicated Cyber Range (CR) specifically designed for comprehensive and repeatable Wi-Fi security training and e…

The paper introduces PriSrv+, an advanced service discovery protocol that significantly enhances privacy, usability, and efficiency in wireless networks through a novel matchmaking encryption scheme c…

This paper provides a comprehensive review of network optimization aspects for Connected and Autonomous Vehicles (CAVs), aiming to clarify misconceptions and outline future research directions.