118 citations · 293 across the 11 of their papers we have counts for
14 papers
Graph Reinforcement Learning for QoS-Aware Load Balancing in Open Radio Access Networks
Omid Semiari, Hosein Nikopour, Shilpa Talwar
Next-generation wireless cellular networks are expected to provide unparalleled Quality-of-Service (QoS) for emerging wireless applications, necessitating strict performance guaran…
Reliability-Optimized User Admission Control for URLLC Traffic: A Neural Contextual Bandit Approach
Omid Semiari, Hosein Nikopour, Shilpa Talwar
Ultra-reliable low-latency communication (URLLC) is the cornerstone for a broad range of emerging services in next-generation wireless networks. URLLC fundamentally relies on the n…
Integrated Access and Backhaul in Millimeter-Wave Cellular: Benefits and Challenges
Yekaterina Sadovaya, Dmitri Moltchanov, Wei Mao +5
The recently proposed NR-ready integrated access and backhaul (IAB) architecture promises to bring a cost-efficient deployment solution for both coverage extension and capacity boo…
Connection Management xAPP for O-RAN RIC: A Graph Neural Network and Reinforcement Learning Approach
Oner Orhan, Vasuki Narasimha Swamy, Thomas Tetzlaff +3
Connection management is an important problem for any wireless network to ensure smooth and well-balanced operation throughout. Traditional methods for connection management (speci…
6G: Connectivity in the Era of Distributed Intelligence
Shilpa Talwar, Nageen Himayat, Hosein Nikopour +3
The confluence of 5G and AI is transforming wireless networks to deliver diverse services at the Edge, driving towards a vision of pervasive distributed intelligence. Future 6G net…
Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks
Saurav Prakash, Sagar Dhakal, Mustafa Akdeniz +4
Federated learning enables training a global model from data located at the client nodes, without data sharing and moving client data to a centralized server. Performance of federa…