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深度学习通信领域相关经典论文、数据集整理分享

深度学习与NLP • 3 年前 • 562 次点击  


    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



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