mhalawad

MIMO_OFDM

《MIMO-OFDM无线通信技术及MATLAB实现》随书源码

AE-Com-Roadmap

Collections of Papers and Codes about Communication Systems Built by Autoencoder

Autoencoder_communication_system_WGAN_Channel-estimation

Master Thesis compairing Communicationsystems Baised on GAN and baised on MI

Deep-Learning-and-Communications-Systems

Related to ECE 766 term project

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

DeepLearningEnabledSemanticCommunicationSystems

dit

Python package for information theory.

End-to-End-Learning-of-Communications-Systems-Without-a-Channel-Model

Implementation of research paper: End-to-End Learning of Communications Systems Without a Channel Model

End2End_GAN

Conditional GAN based End-to-End Communication System

examples

TensorFlow examples

federated

A framework for implementing federated learning

FL-SNN

Code for Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence

LIS-DeepLearning

Simulation code for "Enabling Large Intelligent Surfaces with Compressive Sensing and Deep Learning" by Abdelrahman Taha, Muhammad Alrabeiah, Ahmed Alkhateeb, arXiv e-prints, p. arXiv:1904.10136, Apr 2019.

Master-Thesis

Source Code to my master's thesis with the topic "End-to-end optimisation of MIMO systems using deep learning autoencoders"

meta-autoencoder

Code for the paper "Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels"

meta-demodulator

Code for the paper "Learning to Demodulate from Few Pilots via Offline and Online Meta-Learning"

ML_WirelessComm

Machine Learning Applications in Wireless Communications - Project work

ofdm_im

OFDM with Index Modulation (OFDM-IM) with various detection types and imperfect CSI

python-cheatsheet

Comprehensive Python Cheatsheet

TensorFlow-2.x-Tutorials

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

turboae

Code for "Turbo Autoencoder: Deep learning based channel code for point-to-point communication channels" NeurIPS 2019

Aalto-DL-for-Physical-Layer

An Introduction to Deep Learning for the Physical Layer vs End-to-End Learning of Communications Systems Without a Channel Model

ALAE

[CVPR2020] Adversarial Latent Autoencoders

autoencoder-ofdm-mimo1

autoencoder_for_physical_layer-1

This is my attempt to reproduce and extend the results in the paper "An Introduction to Deep Learning for the Physical Layer" by Tim O'Shea and Jakob Hoydis

Hands-On-Meta-Learning-With-Python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

meta-autoencoder-without-channel-model

Code for the paper "End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-Learning"

ml-with-python-and-keras

Based off Deep Learning with Python by François Chollet

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

PaperProject

This PaperProject is for my paper, there are so many scripts, to store and control the diffierent versions of scripts.