liucaouw

SLU-Simulation

Simulation and analysis code for paper "Sidelink Mode 2 in Unlicensed Bands: Basic Throughput Model & Validation"

PHY_abstraction_V2X_technologies-IEEE-802.11p-IEEE802.11bd-LTE-V2X-NR-V2X-

This repository contain the code of PHY abstraction for current V2X technologies

V2V-Groupcast

liquid_time_constant_networks

Code Repository for Liquid Time-Constant Networks (LTCs)

pytorch-soft-actor-critic

PyTorch implementation of soft actor critic

Awesome-Federated-Learning

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

v2x-lte

millicar

MilliCar - An ns-3 Module for mmWave NR V2X Networks

psc-ns3

Public Safety Communication modeling tools based on ns-3

Deep-Reinforcement-Learning-for-Dynamic-Spectrum-Access

Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication

MARLspectrumSharingV2X

Spectrum sharing in vehicular networks based on multi-agent reinforcement learning, IEEE Journal on Selected Areas in Communications

DynamicMultiChannelRL

Contains Implementation of Paper " S Wang, H Liu, P H Gomes, and B Krishnamachari ; Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks"

qfnet

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

TPC_D2D

Transmit Power Control Using Deep Neural Network for Underlay Device-to-Device Communication

ResourceAllocationReinforcementLearning

intial version

vanet_toolbox

Vehicular Network Simulator in MATLAB/Simulink Environment based on Discrete-event System. https://www.youtube.com/watch?v=wIohwbSk68I&t=47s

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

deeplearning.ai

Some work of Andrew Ng's course on Coursera

Andrew-Ng-Deep-Learning-notes

吴恩达《深度学习》系列课程笔记及代码 | Notes in Chinese for Andrew Ng Deep Learning Course

DeepLearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

ResourceAllocationV2X

Resource allocation for D2D-enabled vehicular communications, IEEE Transactions on Communications

ResourceAllocationV2Xgraph

Graph-based resource sharing in vehicular communication, IEEE Transactions on Wireless Communications

LabelMark

A photo and video marking tools for data generation.

ns3-ai

Enable the interaction between ns-3 and popular frameworks using Python, which mean you can train and test your AI algorithms in ns-3 without changing any frameworks you are using now!

LabelMark

A Label Mark tool using for deep learning

ns-3_c-v2x

Cellular Vehicle-to-Everything (C-V2X) Mode 4 model for ns-3

C-V2X

Analytical Models of the Performance of C-V2X Mode 4 Vehicular Communications