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Found 5 papers, 3 papers with code
Deep Learning Predictive Band Switching in Wireless Networks
Our proposed classifier-based band switching policy instead exploits spatial and spectral correlation between radio frequency signals in different bands based on knowledge of the UE location.
A Framework for Automated Cellular Network Tuning with Reinforcement Learning
In this paper, we formulate cellular network performance tuning as a reinforcement learning (RL) problem and provide a solution to improve the performance for indoor and outdoor environments.
Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells
We propose a reinforcement learning (RL) based closed loop power control algorithm for the downlink of the voice over LTE (VoLTE) radio bearer for an indoor environment served by small cells.
Deep Q-Learning for Self-Organizing Networks Fault Management and Radio Performance Improvement
We propose an algorithm to automate fault management in an outdoor cellular network using deep reinforcement learning (RL) against wireless impairments.
Machine Learning in Downlink Coordinated Multipoint in Heterogeneous Networks
We propose a method for downlink coordinated multipoint (DL CoMP) in heterogeneous fifth generation New Radio (NR) networks.
