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With the development of deep learning, more and more research has been done to solve problems in related communication fields using deep learning. As a graduate student in communications, if the lab does not have the code to accumulate in the relevant direction, it will be very difficult to get started and go deep into a new direction. At the same time, most papers in the field of communication do not provide open source code, and reproducible research is difficult.
The communication papers based on deep learning have increased rapidly in recent years, and the authors of these papers are more willing to open source. This project focuses on the collection of papers which are relevant to wireless communication based on deep learning and released the code .
The area of personal attention and limited efforts, this list will not be so complete. If you know some related open source papers, but not on this list, you are welcome to pull request.

TODO

  • Sort by different subdirections
  • Add download link to paper
  • Add more related paper's code
  • Traditional communication paper code list
  • "Communication +DL" paper list (high cited, without code is ok)
Paper Code
DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications The DeepMIMO Dataset
Turbo Autoencoder: Deep learning based channel code for point-to-point communication channels yihanjiang/turboae
Communication Algorithms via Deep Learning yihanjiang/commviadl
Fast Deep Learning for Automatic Modulation Classification dl4amc/source
Deep Learning-Based Channel Estimation Mehran-Soltani/ChannelNet
Transmit Power Control Using Deep Neural Network for Underlay Device-to-Device Communication seotaijiya/TPC_D2D
Deep learning-based channel estimation for beamspace mmWave massive MIMO systems hehengtao/LDAMP_based-Channel-estimation
Spatial deep learning for wireless scheduling willtop/Spatial_DeepLearning_Wireless_Scheduling
Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach swordest/mec_drl
A deep-reinforcement learning approach for software-defined networking routing optimization knowledgedefinednetworking / a-deep-rl-approach-for-sdn-routing-optimization
Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells farismismar / Q-Learning-Power-Control
Deep Learning for Optimal Energy-Efficient Power Control in Wireless Interference Networks bmatthiesen / deep-EE-opt
Actor-Critic-Based Resource Allocation for Multi-modal Optical Networks BoyuanYan / Actor-Critic-Based-Resource-Allocation-for-Multimodal-Optical-Networks
Deep MIMO Detection neevsamuel/DeepMIMODetection
Learning to Detect neevsamuel/LearningToDetect
An iterative BP-CNN architecture for channel decoding liangfei-info/Iterative-BP-CNN
On Deep Learning-Based Channel Decoding gruberto/DL-ChannelDecoding
DELMU: A Deep Learning Approach to Maximising the Utility of Virtualised Millimetre-Wave Backhauls ruihuili / DELMU
Deep Q-Learning for Self-Organizing Networks Fault Management and Radio Performance Improvement farismismar / Deep-Q-Learning-SON-Perf-Improvement
An Introduction to Deep Learning for the Physical Layer yashcao / RTN-DL-for-physical-layer
musicbeer / Deep-Learning-for-the-Physical-Layer
helloMRDJ / autoencoder-for-the-Physical-Layer
Convolutional Radio Modulation Recognition Networks chrisruk/cnn
qieaaa / Singal-CNN
Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex Convolutional Networks zhongyuanzhao / dl_ofdm
Joint Transceiver Optimization for WirelessCommunication PHY with Convolutional NeuralNetwork hlz1992/RadioCNN
Deep Learning for Massive MIMO CSI Feedback sydney222 / Python_CsiNet
Beamforming Design for Large-Scale Antenna Arrays Using Deep Learning TianLin0509/BF-design-with-DL
5G MIMO Data for Machine Learning: Application to Beam-Selection using Deep Learning lasseufpa/5gm-data
Deep multi-user reinforcement learning for dynamic spectrum access in multichannel wireless networks shkrwnd/Deep-Reinforcement-Learning-for-Dynamic-Spectrum-Access
DeepNap: Data-Driven Base Station Sleeping Operations through Deep Reinforcement Learning zaxliu/deepnap
Automatic Modulation Classification: A Deep Learning Enabled Approach mengxiaomao/CNN_AMC
Deep Architectures for Modulation Recognition qieaaa / Deep-Architectures-for-Modulation-Recognition
Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks mkoz71 / Energy-Efficiency-in-Reinforcement-Learning
Learning to optimize: Training deep neural networks for wireless resource management Haoran-S / DNN_WMMSE
Implications of Decentralized Q-learning Resource Allocation in Wireless Networks wn-upf / decentralized_qlearning_resource_allocation_in_wns
Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems haoyye/OFDM_DNN

Contributors:

WxZhu

Updates:

  1. complete first version :2019-02-21