nangszml

qfnet

《Power Allocation in Multi-cell Networks Using Deep Reinforcement Learning》论文复现

Power-Allocation-and-User-Device-Association-with-Deep-Reinforcement-Learning

uav-deep-q

This is the source code using deep Q learning for calculate UAV resource allocation

LMO-DDPG_WZJ

An optimized DDPG algorithm for autonomous path planning of UAV in network-unavailable environment

DRL_UAV_CellularNet

Simulator developed for the mobility management of UAV base stations project featuring A3C

UAV-A3C

using actor-critic method to dealing with the path-planning UAV problem

Spectrum-Power-Allocation

Deep Reinforcement Learning for Joint Spectrum and Power Allocation in Cellular Networks code

Paper-code-for-Machine-Learning-based-Wireless-Communication-Optimization-Problems

A collection for Paper/code for Wireless Communication Optimization Problems with PyTorch based DL

DeepCoMP

Dynamic multi-cell selection for cooperative multipoint (CoMP) using (multi-agent) deep reinforcement learning

Allocation-policy-ddpg

mec_alloc_rl

User allocation in Mobile Edge Computing Environment using Reinforcement Learning

UAV_RL_Maximize_Throughput

UAV-based MEC to maximize user throughput via reinforcement learning

DHDRL

Distributed Two-tier DRL Framework for Cell-Free Network: Association, Beamforming and Power Allocation

AFLDDPG

* Wu Q, Wang S, Fan P, et al. Deep Reinforcement Learning Based Vehicle Selection for Asynchronous Federated Learning Enabled Vehicular Edge Computing[J]. arXiv preprint arXiv:2304.02832, 2023. 链接： https://arxiv.org/abs/2304.02832 代码： https://github.com/qiongwu86/AFLDDPG

UserAssociation

This repository consists of codes for the Policy based User Association method that is being developed

Joint-User-Association-and-In-band-Backhaul-Scheduling-and-in-5G-mmWave-Networks

Matlab Simulation for T. K. Vu, M. Bennis, S. Samarakoon, M. Debbah and M. Latva-aho, "Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks," European Wireless 2016; 22th European Wireless Conference, Oulu, Finland, 2016, pp. 1-6. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7499273&isnumber=7499250

UARA-DRL

This repository contains the implementation codes of deep reinforcement learning (DRL) in user association and resource allocation in heterogenous networks. The model is basd on deep-Q-network (DQN) and DDQN.

Spectrum-Power-Allocation

Deep Reinforcement Learning for Joint Spectrum and Power Allocation in Cellular Networks code

Power-Control-asilomar

Asilomar 2020 code for Deep Actor-Critic Learning for Distributed Power Control in Wireless Mobile Networks

UAV-Navigation-Learning

DeepRL-mmWave-MANET

In this work, reinforce learning techniques like Deep Reinforcement Learning (PPO) and Multi-armed bandit are exploited to design mmWave MANET user scheduling and transmission configuration.

Top-AI-Conferences-Paper-with-Code

MLNLP: This repository is a collection of AI top conferences papers (e.g. ACL, EMNLP, NAACL, COLING, AAAI, IJCAI, ICLR, NeurIPS, and ICML) with open resource code

docs

TensorFlow documentation

Paper-with-Code-of-Wireless-communication-Based-on-DL

无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL

UARA

J. Liu, X. Tao and J. Lu, "Mobility-Aware Centralized Reinforcement Learning for Dynamic Resource Allocation in HetNets," accepted by IEEE GLOBECOM 2019.

IBM-Data-Engineer-Specialization-Coursera-Personal-Note-Public

All of my individual learning materials, documents, and notes from the process of getting the Coursera IBM Data Engineer Professional Certificate specialization are stored in this repository.

Resource-Allocation-using-deeprl

Deep Reinforcement Learning Based Dynamic Resource Allocation in 5G Ultra-Dense Networks