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20192022
most citedDistributed Scheduling using Graph Neural Networks

6 citations · 11 across the 4 of their papers we have counts for

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eess.SP2021

Link Scheduling using Graph Neural Networks

Zhongyuan Zhao, Gunjan Verma, Chirag Rao +2

Efficient scheduling of transmissions is a key problem in wireless networks. The main challenge stems from the fact that optimal link scheduling involves solving a maximum weighted…

eess.SP2020

Efficient power allocation using graph neural networks and deep algorithm unfolding

Arindam Chowdhury, Gunjan Verma, Chirag Rao +2

We study the problem of optimal power allocation in a single-hop ad hoc wireless network. In solving this problem, we propose a hybrid neural architecture inspired by the algorithm…

eess.SP2020

Adaptive Contention Window Design using Deep Q-learning

Abhishek Kumar, Gunjan Verma, Chirag Rao +2

We study the problem of adaptive contention window (CW) design for random-access wireless networks. More precisely, our goal is to design an intelligent node that can dynamically a…

eess.SP2020★ 6 cited

Distributed Scheduling using Graph Neural Networks

Zhongyuan Zhao, Gunjan Verma, Chirag Rao +2

A fundamental problem in the design of wireless networks is to efficiently schedule transmission in a distributed manner. The main challenge stems from the fact that optimal link s…

eess.SP2020

Unfolding WMMSE using Graph Neural Networks for Efficient Power Allocation

Arindam Chowdhury, Gunjan Verma, Chirag Rao +2

We study the problem of optimal power allocation in a single-hop ad hoc wireless network. In solving this problem, we depart from classical purely model-based approaches and propos…

eess.SP2019

Directional Communication Enabled by Mobile Parasitic Elements

Fikadu T. Dagefu, Jeffrey N. Twigg, Chirag R. Rao +1

Mobile communications in complex environments such as mega-cities is a challenging problem that limits the ability to deploy autonomous agents in support of operations. Building on…