Aug 6, 2018 · This paper proposes an innovative scheduling framework able to select different scheduling rules according to instantaneous scheduler states.

Transactions on Network and Service Management. 1. Towards 5G: A Reinforcement Learning-based. Scheduling Solution for Data Traffic Management. Ioan-Sorin Coms ...

Aug 3, 2018 · To deal with real-time scheduling, the Reinforcement Learning (RL) principles are used to map the scheduling rules to each state and to learn ...

In this context, the packet scheduler plays a central role by allocating user data packets in the frequency domain at each predefined time interval. Standard ...

An innovative scheduling framework able to select different scheduling rules according to instantaneous scheduler states in order to minimize the packet ...

Towards 5G: A reinforcement learning-based scheduling solution for data traffic management ; IEEE · IEEE Transactions on Network and Service Management · 1932-4537.

The paper is aimed to develop and show the performance of RL PGagent based scheduler of the air interface resources in 5G networks. The performance of the ...

In this paper we leverage the benefits of machine learning for solving the complex RRM problem of 5G NR by designing a DQN-based downlink scheduler. The goal of ...

This paper proposes a new method, namely Vehicle-to-Infrastructure based Traffic Signal Control (V2I-TSC), to capture realistic traffic state.

Jun 15, 2023 · An efficient 5G-TSN joint scheduling algorithm based on Deep Deterministic Policy Gradient (DDPG) is proposed and analyzed in this article.