Deep Reinforcement Learning for QoS-Constrained Resource Allocation in Multiservice Networks

no code implementations • 3 Mar 2020 • Juno V. Saraiva, Iran M. Braga Jr., Victor F. Monteiro, F. Rafael M. Lima, Tarcisio F. Maciel, Walter C. Freitas Jr., F. Rodrigo P. Cavalcanti

In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-convex optimization problem whose main aim is to maximize the spectral efficiency subject to satisfaction guarantees in multiservice wireless systems.

Distributed Optimization reinforcement-learning +1

Adaptive Modulation and Coding based on Reinforcement Learning for 5G Networks

no code implementations • 25 Nov 2019 • Mateus P. Mota, Daniel C. Araujo, Francisco Hugo Costa Neto, Andre L. F. de Almeida, F. Rodrigo P. Cavalcanti

We design a self-exploratory reinforcement learning (RL) framework, based on the Q-learning algorithm, that enables the base station (BS) to choose a suitable modulation and coding scheme (MCS) that maximizes the spectral efficiency while maintaining a low block error rate (BLER).

Q-Learning reinforcement-learning +1