Pinned Repositories
d2dflow-simulation
Simulations of D2DFlow protocol
d2dsimulator
D2D communications system simulator on MATLAB.
d2l-en
Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook. With code, math, and discussions.
decentralized_qlearning_resource_allocation_in_wns
deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
Deep-Reinforcement-Learning-for-5G-Networks
Code for my publication: Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination. Paper under review.
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
Device-to-device
服务D2D、V2V仿真
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
Q-Learning-Power-Control
Code for my publication: Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells. Paper accepted to IEEE 52nd Asilomar Conference on Signals, Systems, and Computers.
wlglixin's Repositories
wlglixin/Q-Learning-Power-Control
Code for my publication: Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells. Paper accepted to IEEE 52nd Asilomar Conference on Signals, Systems, and Computers.
wlglixin/d2dflow-simulation
Simulations of D2DFlow protocol
wlglixin/d2dsimulator
D2D communications system simulator on MATLAB.
wlglixin/d2l-en
Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook. With code, math, and discussions.
wlglixin/decentralized_qlearning_resource_allocation_in_wns
wlglixin/deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
wlglixin/Deep-Reinforcement-Learning-for-5G-Networks
Code for my publication: Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination. Paper under review.
wlglixin/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
wlglixin/Device-to-device
服务D2D、V2V仿真
wlglixin/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
wlglixin/PeerRead
Data and code for Kang et al., NAACL 2018's paper titled "A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications"
wlglixin/proximity
Power allocation in a dense cellular network using Q-learning
wlglixin/py-wireless-sys-sim
wlglixin/qfnet
《Power Allocation in Multi-cell Networks Using Deep Reinforcement Learning》论文复现
wlglixin/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
wlglixin/RF_gym
MIMO Env using Reinforcement Learning
wlglixin/Search_a_Paper_in_SEU_for_CSE
本文档适合于刚入学的东南大学硕士和博士(计算机专业最好，其他专业可参考)。
wlglixin/TPC_D2D
Transmit Power Control Using Deep Neural Network for Underlay Device-to-Device Communication