452 citations · 818 across the 40 of their papers we have counts for
10 papers · 1 filter
Long-Horizon Wireless Link Scheduling with State-Augmented Graph Neural Networks
Romina Garcia Camargo, Zhiyang Wang, Navid NaderiAlizadeh +1
We address optimal link scheduling in large-scale wireless networks. The goal is to schedule transmissions over a time horizon so that to maximize sum rate while ensuring that aver…
Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression
Yigit Berkay Uslu, Navid NaderiAlizadeh, Mark Eisen +1
We consider resource allocation problems in multi-user wireless networks, where the goal is to optimize a network-wide utility function subject to constraints on the ergodic averag…
Wireless Link Scheduling with State-Augmented Graph Neural Networks
Romina Garcia Camargo, Zhiyang Wang, Navid NaderiAlizadeh +1
We consider the problem of optimal link scheduling in large-scale wireless ad hoc networks. We specifically aim for the maximum long-term average performance, subject to a minimum…
Opportunistic Routing in Wireless Communications via Learnable State-Augmented Policies
Sourajit Das, Kirtan Gopal Panda, Navid NaderiAlizadeh
This paper addresses the challenge of packet-based information routing in large-scale wireless communication networks. The problem is framed as a constrained statistical learning t…
Learning to Slice Wi-Fi Networks: A State-Augmented Primal-Dual Approach
Yiğit Berkay Uslu, Roya Doostnejad, Alejandro Ribeiro +1
Network slicing is a key feature in 5G/NG cellular networks that creates customized slices for different service types with various quality-of-service (QoS) requirements, which can…
Transferable Graphical MARL for Real-Time Estimation in Dynamic Wireless Networks
Xingran Chen, Navid NaderiAlizadeh, Alejandro Ribeiro +1
We study real-time sampling and estimation of autoregressive Markovian sources in decentralized and dynamic multi-hop networks that share similar structures. Nodes cache neighborin…
Learning Resilient Radio Resource Management Policies with Graph Neural Networks
Navid NaderiAlizadeh, Mark Eisen, Alejandro Ribeiro
We consider the problems of user selection and power control in wireless interference networks, comprising multiple access points (APs) communicating with a group of user equipment…
Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels
Navid Naderializadeh
We consider the problem of binary power control, or link scheduling, in wireless interference networks, where the power control policy is trained using graph representation learnin…
Contrastive Self-Supervised Learning for Wireless Power Control
Navid Naderializadeh
We propose a new approach for power control in wireless networks using self-supervised learning. We partition a multi-layer perceptron that takes as input the channel matrix and ou…
Wireless Power Control via Counterfactual Optimization of Graph Neural Networks
Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
We consider the problem of downlink power control in wireless networks, consisting of multiple transmitter-receiver pairs communicating with each other over a single shared wireles…