随着深度学习的发展，使用深度学习解决相关通信领域问题的研究也越来越多。作为一名通信专业的研究生，如果实验室没有相关方向的代码积累，入门并深入一个新的方向会十分艰难。同时，大部分通信领域的论文不会提供开源代码，reproducible research比较困难。
基于深度学习的通信论文这几年飞速增加，明显能感觉这些论文的作者更具开源精神。本项目专注于整理在通信中应用深度学习，并公开了相关源代码的论文。
本文资源整理自网络，源地址：https://github.com/IIT-Lab/Paper-with-Code-of-Wireless-communication-Based-on-DL
论文列表
Deep Learning for SVD and Hybrid Beamforming
Neural Mutual Information Estimation for Channel Coding: State-of-the-Art Estimators, Analysis, and Performance Comparison
Deep Transfer Learning Based Downlink Channel Prediction for FDD Massive MIMO Systems
Channel Estimation for One-Bit Multiuser Massive MIMO Using Conditional GAN
A Model-Driven Deep Learning Method for Normalized Min-Sum LDPC Decoding
Complex-Valued Convolutions for Modulation Recognition using Deep Learning
Enabling Large Intelligent Surfaces with Compressive Sensing and Deep Learning
Wireless link adaptation - a hybrid data-driven and model-based approac
hDeep unfolding of the weighted MMSE algorithm
Learn to Compress CSI and Allocate Resources in Vehicular Networks
Benchmarking End-to-end Learning of MIMO Physical-Layer Communication
Learned Conjugate Gradient Descent Network for Massive MIMO Detection
Trainable Projected Gradient Detector for Massive Overloaded MIMO Channels: Data-driven Tuning Approac
hDeep Soft Interference Cancellation for MIMO Detection
Reinforcement Learning Based Scheduling Algorithm for Optimizing Age of Information in Ultra Reliable Low Latency Networks
Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design
MaMIMO CSI-based positioning using CNNs: Peeking inside the black box
Learning Combinatorial Optimization Algorithms over Graphs
Extending the RISC-V ISA for Efficient RNN-based 5G Radio Resource Management
Power Allocation in Multi-user Cellular Networks With Deep Q Learning Approac
hPower Allocation in Multi-User Cellular Networks: Deep Reinforcement Learning Approaches
Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
Federated Learning over Wireless Networks: Optimization Model Design and Analysis
Deep learning based end-to-end wireless communication systems with conditional GAN as unknown channel
Intelligent Resource Allocation in Wireless Communications Systems
Spatio-Temporal Representation with Deep Recurrent Network in MIMO CSI Feedback
Neural Network Aided SC Decoder for Polar Codes
Exploiting Bi-Directional Channel Reciprocity in Deep Learning for Low Rate Massive MIMO CSI Feedback
Performance Evaluation of Channel Decoding With Deep Neural Networks
Learning the MMSE Channel Estimator
Deep Deterministic Policy Gradient (DDPG)-Based Energy Harvesting Wireless Communications
Model-Aware Deep Architectures for One-Bit Compressive Variational Autoencoding
CSI-based Positioning in Massive MIMO systems using Convolutional Neural Networks
Deep Learning for mmWave Beam and Blockage Prediction Using Sub-6GHz Channels
Deep Learning for Channel Coding via Neural Mutual Information Estimation
Deep Learning for the Gaussian Wiretap Channel
Multi-resolution CSI Feedback with deep learning in Massive MIMO System
Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks
Mobility-Aware Centralized Reinforcement Learning for Dynamic Resource Allocation in HetNets
Deep Learning for Direct Hybrid Precoding in Millimeter Wave Massive MIMO Systems
Deep Learning-Based Detector for OFDM-IM
Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels
Learning to Communicate in a Noisy Environment
Low-rank mmWave MIMO channel estimation in one-bit receivers
Deep Learning for Massive MIMO with 1-Bit ADCs: When More Antennas Need Fewer Pilots
ns-3 meets OpenAI Gym: The Playground for Machine Learning in Networking Researc
hTurbo Autoencoder: Deep learning based channel code for point-to-point communication channels
Communication Algorithms via Deep Learning
Towards Optimal Power Control via Ensembling Deep Neural Networks
Low-Precision Neural Network Decoding of Polar Codes
A Graph Neural Network Approach for Scalable Wireless Power Control
CNN-based Precoder and Combiner Design in mmWave MIMO Systems
Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
An Open-Source Framework for Adaptive Traffic Signal Control
A CNN-Based End-to-End Learning Framework Towards Intelligent Communication Systems
Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding
Adaptive Neural Signal Detection for Massive MIMO
Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks
Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells
Spectrum sharing in vehicular networks based on multi-agent reinforcement learning
Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors
Learning Physical-Layer Communication with Quantized Feedback
Decentralized Scheduling for Cooperative Localization with Deep Reinforcement Learning
Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks
MIST: A Novel Training Strategy for Low-latencyScalable Neural Net Decoders
Deep UL2DL: Channel Knowledge Transfer from Uplink to Downlink
Deep Learning for TDD and FDD Massive MIMO: Mapping Channels in Space and Frequency
Machine Learning meets Stochastic Geometry: Determinantal Subset Selection for Wireless Networks
Learning Based Power Control for mmWave Massive MIMO against Jamming
Sparsely Connected Neural Network for Massive MIMO Detection
Power Allocation in Multi-Cell Networks Using Deep Reinforcement Learningg
Deep Learning in Downlink Coordinated Multipoint in New Radio Heterogeneous Networks
Deep Reinforcement Learning for Resource Allocation in V2V Communications
RF-based Direction Finding of UAVs Using DNN
Deepcode: Feedback Codes via Deep Learning
Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems
AIF: An Artificial Intelligence Framework for Smart Wireless Network Management
Deep-Learning-Power-Allocation-in-Massive-MIMO
DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications
Fast Deep Learning for Automatic Modulation Classification
Deep Learning-Based Channel Estimation
Transmit Power Control Using Deep Neural Network for Underlay Device-to-Device Communication
Deep learning-based channel estimation for beamspace mmWave massive MIMO systems
Spatial deep learning for wireless scheduling
Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approac
hA deep-reinforcement learning approach for software-defined networking routing optimization
Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells
Deep Learning for Optimal Energy-Efficient Power Control in Wireless Interference Networks
Actor-Critic-Based Resource Allocation for Multi-modal Optical Networks
Deep MIMO Detection
Learning to Detect
An iterative BP-CNN architecture for channel decoding
On Deep Learning-Based Channel Decoding
DELMU: A Deep Learning Approach to Maximising the Utility of Virtualised Millimetre-Wave Backhauls
Deep Q-Learning for Self-Organizing Networks Fault Management and Radio Performance Improvement
An Introduction to Deep Learning for the Physical Layer
Convolutional Radio Modulation Recognition Networks
Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex Convolutional Networks
Joint Transceiver Optimization for WirelessCommunication PHY with Convolutional NeuralNetwork
Deep Learning for Massive MIMO CSI Feedback
Beamforming Design for Large-Scale Antenna Arrays Using Deep Learning
5G MIMO Data for Machine Learning: Application to Beam-Selection using Deep Learning
Deep multi-user reinforcement learning for dynamic spectrum access in multichannel wireless networks
DeepNap: Data-Driven Base Station Sleeping Operations through Deep Reinforcement Learning
Automatic Modulation Classification: A Deep Learning Enabled Approac
hDeep Architectures for Modulation Recognition
Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks
Learning to optimize: Training deep neural networks for wireless resource management
Implications of Decentralized Q-learning Resource Allocation in Wireless Networks
Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems
数据集
MASSIVE MIMO CSI MEASUREMENTS
SM-CsiNet+ and PM-CsiNet+:来自论文Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis
An open online real modulated dataset:来自论文Deep Learning for Signal Demodulation in Physical Layer Wireless Communications: Prototype Platform, Open Dataset, and Analytics。
To the best of our knowledge,this is the first open dataset of real modulated signals for wireless communication systems.
RF DATASETS FOR MACHINE LEARNING
open datase:来自论文Signal Demodulation With Machine Learning Methods for Physical Layer Visible Light Communications: Prototype Platform, Open Dataset, and Algorithms