most citedLatency Fairness Optimization on Wireless Networks through Deep Reinforcement Learning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.IT2024

Optimizing MIMO Efficiency in 5G through Precoding Matrix Techniques

Francisco Díaz-Ruiz, Francisco J. Martín-Vega, Gerardo Gómez +1

Multiple-Input Multiple-Output (MIMO) systems play a crucial role in fifth-generation (5G) mobile communications, primarily achieved through the utilization of precoding matrix tec…

cs.IT2022★ 2 cited

Latency Fairness Optimization on Wireless Networks through Deep Reinforcement Learning

M. López-Sánchez, A. Villena-Rodríguez, G. Gómez +2

In this paper, we propose a novel deep reinforcement learning framework to maximize user fairness in terms of delay. To this end, we devise a new version of the modified largest we…