In this paper, we propose a reinforcement learning-based framework to solve scheduling problems with the main focus on meeting the user fairness requirements.
A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers · Abstract. Due to large-scale control problems in 5G access networks, ...
A reinforcement learning-based framework to solve scheduling problems with the main focus on meeting the user fairness requirements is proposed, ...
In this paper, we propose a reinforcement learning-based framework to solve scheduling problems with the main focus on meeting the user fairness requirements.
In this paper, we propose a reinforcement learning-based framework to solve scheduling problems with the main focus on meeting the user fairness requirements.
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Reinforcement learning is seen as a promising solution ... schedulers oriented on fairness objective ... OFDMA schedulers > Accès aux Fichiers. ArODES.
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[PDF] Multi-Agent Reinforcement Learning-Based Fairness-Aware ...
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Abstract—In this work, we develop practical user scheduling algorithms for downlink bursty traffic with emphasis on user fairness.
May 14, 2024 · A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers. Information, 10(10): 315. Corbett-Davies and Goel ...