Stars
Optimization of resource allocation in heterogeneous wireless networks using deep reinforcement learning.
Machine learning-augmented resource allocation framework for energy-efficient 6G wireless systems. Combines LSTM/Transformer predictions with classical optimization algorithms for improved throughp…
Deep Reinforcement Learning Based Dynamic Resource Allocation in 5G Ultra-Dense Networks
GNN-Based Joint Channel and Power Allocation in Heterogeneous Wireless Networks
Energy-Efficient Power and Subcarrier Allocation for OFDMA Systems with Value Function Approximation Approach. EI paper from march to september 2012.
Joint Subcarrier and Power Allocation algorithms for WSR maximization in NOMA published in IEEE TSP 2020
This contains joint channel and power allocation scheme for a full duplex cognitive radio network underlying a cellular network
Deep Q network-based power allocation for multi-cell massive MIMO cellular network.
A Machine Learning Approach for Power Allocation in HetNets Considering QoS
Simulation code for "Downlink Power Control for Cell-Free Massive MIMO with Deep Reinforcement Learning" by Lirui Luo, Jiayi Zhang, Shuaifei Chen, Bo Ai, and Derrick Wing Kwan Ng, IEEE Transactions…
Deep Reinforcement Learning for Joint Spectrum and Power Allocation in Cellular Networks code
The source code for Performance comparision of Deep RL algorithms for Energy Systems Optimal Scheduling
Deep Reinforcement Learning Based Dynamic Resource Allocation in 5G Ultra-Dense Networks
J. Liu, X. Tao and J. Lu, "Mobility-Aware Centralized Reinforcement Learning for Dynamic Resource Allocation in HetNets," accepted by IEEE GLOBECOM 2019.
20220427-use DQN and DDPG to allocation the NOMA resource
Deep reinforcement learning algorithms implemented using PyTorch, including DQN、DDPG、PPO、SAC、DDQN、Noisy-DQN.
An intelligent task offloading method based on multi-agent deep reinforcement learning in ultra-dense heterogeneous network with mobile edge computing
UAV-based Cellular-Communication: Multi-Agent Deep Reinforcement Learning for Interference Management
Distributed Two-tier DRL Framework for Cell-Free Network: Association, Beamforming and Power Allocation
Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems
Implementation of: Nazari, Mohammadreza, et al. "Deep Reinforcement Learning for Solving the Vehicle Routing Problem." arXiv preprint arXiv:1802.04240 (2018).
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning https://arxiv.org/abs/1611.09940
Using GitHub Action to collect paper list with publicly available source code in the daily arxiv