5 papers
Measurement-Driven Early Warning of Reliability Breakdown in 5G NSA Railway Networks
Po-Heng Chou, Da-Chih Lin, Hung-Yu Wei +2
This paper presents a measurement-driven study of early warning for reliability breakdown events in 5G non-standalone (NSA) railway networks. Using 10~Hz metro-train measurement tr…
EVT-Based Generative AI for Tail-Aware Channel Estimation
Parmida Valiahdi, Niloofar Mehrnia, Walid Saad +1
Ultra-reliable and low-latency communication (URLLC) will play a key role in fifth-generation (5G) and beyond networks, enabling mission-critical applications. Meeting the stringen…
Neurosymbolic Learning for Advanced Persistent Threat Detection under Extreme Class Imbalance
Quhura Fathima, Neda Moghim, Mostafa Taghizade Firouzjaee +3
The growing deployment of Internet of Things (IoT) devices in smart cities and industrial environments increases vulnerability to stealthy, multi-stage advanced persistent threats…
Agentic DDQN-Based Scheduling for Licensed and Unlicensed Band Allocation in Sidelink Networks
Po-Heng Chou, Pin-Qi Fu, Walid Saad +1
In this paper, we present an agentic double deep Q-network (DDQN) scheduler for licensed/unlicensed band allocation in New Radio (NR) sidelink (SL) networks. Beyond conventional re…
Green Learning for STAR-RIS mmWave Systems with Implicit CSI
Yu-Hsiang Huang, Po-Heng Chou, Wan-Jen Huang +2
In this paper, a green learning (GL)-based precoding framework is proposed for simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided millim…