Kim jinwook's Projects
Unofficial Pytorch implementation of Deep Learning-Based MIMO Communications (Timothy J. OβShea)
Source code for paper deepjscc-l++
Implementation of "Distributed Deep Joint Source-Channel Coding with Decoder-Only Side Information" paper (ICMLCN 2024)
Code for "Deep MIMO detection"
Code for "Deep Learning Enabled Semantic Communication Systems"
Pytorch implementation of the DeepSC
Semantic Communication Systems for Speech Transmission
Code for "Deep Learning Enabled Semantic Communications with Speech Recognition and Synthesis"
DT-JSCC: discrete joint source-channel coding for task-oriented communication with digital modulation
This repository includes the source code of the DL-based symbol-by-symbol and frame-by-frame channel estimators proposed in "A Survey on Deep Learning Based Channel Estimation in Doubly Dispersive Environments" paper [1] that is published in the IEEE Access, 2022.
This repository contains the code needed to reproduce results in the paper by M. Belgiovine, et al. βDeep Learning at the Edge for Channel Estimation in Beyond-5G Massive MIMO,β accepted at IEEE Wireless Communications Magazine (WCM), April 2021.
Source codes of the article: "Framework on Deep Learning-Based Joint Hybrid Processing for mmWave Massive MIMO Systems" in IEEE Access.
Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex-valued Convolutional Networks
code for "Deep Neural Network Architectures for Modulation Classification"
Contains the code related to our paper on scheduling and resource allocation in wireless communications.
Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks
Official implementation of Dynamical VAEs
Codes for "Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control", ICASSP 2022
TF Code for "Real-Time Semantic Communications with a Vision Transformer"
Conditional GAN based End-to-End Communication System
Deep energy autoencoder for noncoherent communications
Code for "Environment Semantic Aided Communication: A Real World Demonstration for Beam Prediction"