Multi-Flow Transmission in Wireless Interference Networks: A Convergent Graph Learning Approach

no code implementations • 27 Mar 2023 • Raz Paul, Kobi Cohen, Gil Kedar

The objective is to develop a multi-flow transmission strategy that routes flows across the wireless interference network to maximize the network utility.

Graph Learning Reinforcement Learning (RL)

Using Deep Reinforcement Learning for mmWave Real-Time Scheduling

no code implementations • 4 Oct 2022 • Barak Gahtan, Reuven Cohen, Alex M. Bronstein, Gil Kedar

The most important advantage of AARL compared to RPMA is that it is much faster and can make the necessary scheduling decisions very rapidly during every time slot, while RPMA cannot.

reinforcement-learning Reinforcement Learning (RL) +1