muhd-umer / comyxLinks
Comyx is an optimized and modular Python library for simulating wireless communication systems
☆16Updated 9 months ago
Alternatives and similar repositories for comyx
Users that are interested in comyx are comparing it to the libraries listed below
Sorting:
- Simulation code and accompanying material for the textbook "Introduction to Multiple Antenna Communications and Reconfigurable Surfaces" …☆89Updated last month
- This repository contains the slides to some of my YouTube presentations, as well as some slides and posters from conferences☆63Updated 2 weeks ago
- Book PDF and simulation code for the monograph "Foundations of User-Centric Cell-Free Massive MIMO" by Özlem Tugfe Demir, Emil Björnson a…☆123Updated last year
- Teaching material for wireless communications☆140Updated 6 months ago
- This repository contains the slides (in Powerpoint and PDF formats) for the course Multiple Antenna Communications, used 2021. Video reco…☆69Updated 3 years ago
- Code for M. Polese, J. Jornet, T. Melodia, M. Zorzi, “Toward End-to-End, Full-Stack 6G Terahertz Networks”, https://arxiv.org/abs/2005.07…☆21Updated 5 years ago
- DL tackling Massive-MIMO problems☆48Updated 5 years ago
- ☆71Updated 4 years ago
- Simulation code for “Learning-Based Downlink Power Allocation in Cell-Free Massive MIMO Systems,” by Mahmoud Zaher, Özlem Tuğfe Demir, Em…☆85Updated last year
- Conditional GAN based End-to-End Communication System☆79Updated 4 years ago
- Simulation code for "Unsupervised Deep Learning for Massive MIMO Hybrid Beamforming" by Hamed Hojatian, Jeremy Nadal, Jean-Francois Frigo…☆79Updated 2 years ago
- Implementation of research paper: End-to-End Learning of Communications Systems Without a Channel Model☆36Updated 6 years ago
- Joint Deep Reinforcement Learning and Unfolding: Beam Selection and Precoding for mmWave Multiuser MIMO With Lens Arrays☆49Updated 4 years ago
- ☆81Updated 3 years ago
- Simulation code for “Scalable Cell-Free Massive MIMO Systems,” by Emil Björnson and Luca Sanguinetti, IEEE Transactions on Communications…☆64Updated 4 years ago
- Realization of MIMO-NOMA signal detection system based on **C. Lin et al., “A deep learning approach for MIMO-NOMA downlink signal detect…☆85Updated 4 years ago
- This repository contains the code needed to reproduce results in the paper by M. Belgiovine, et al. “Deep Learning at the Edge for Chann…☆57Updated 2 years ago
- Simulation code for “Intelligent Reflecting Surface vs. Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?,” by Emil Bj…☆113Updated last year
- ☆27Updated 3 years ago
- 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'Sh…☆58Updated 4 years ago
- A MATLAB implementation of an OFDM based Power Domain NOMA System☆98Updated 5 years ago
- Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)☆94Updated 3 years ago
- This repository contains the slides (in Powerpoint and PDF formats) for the course TSKS14 Multiple Antenna Communications, used 2020. Vid…☆36Updated 5 years ago
- Dataset and code for M. Polese, L. Bertizzolo, L. Bonati, A. Gosain, T. Melodia, An Experimental mmWave Channel Model for UAV-to-UAV Comm…☆39Updated 5 years ago
- ML-based channel modeling for millimeter wave wireless communications☆31Updated 4 years ago
- Source code for paper Deep Learning for Direct Hybrid Precoding in Millimeter Wave Massive MIMO Systems☆71Updated 3 years ago
- This is the code package related to the follow scientific article: Luca Sanguinetti, Alessio Zappone, Merouane Debbah 'Deep-Learning-Pow…☆92Updated 5 years ago
- Simulation code for “Reconfigurable Intelligent Surfaces: A Signal Processing Perspective With Wireless Applications” by Emil Björnson, H…☆56Updated 3 years ago
- DeepMIMO (v2 & v3) Python Dataset Framework for mmWave and massive MIMO Research☆80Updated 4 months ago
- Contains MATLAB and Python codes and plots for deriving inferences for various concepts of Wireless Communications.☆14Updated 4 years ago