FenghaoZhu/Matrix-Inverse-Free-WMMSE
This is the code implementation for the Matrix-Inverse-Free MU-MIMO WMMSE Beamforming Algorithm.
This project helps wireless communication engineers optimize multi-user, multiple-input, multiple-output (MU-MIMO) systems. It takes in channel state information and other wireless network parameters to produce optimized beamforming weights. This is designed for researchers and practitioners working on advanced wireless network design and optimization.
No commits in the last 6 months.
Use this if you are developing or simulating MU-MIMO systems and need an efficient way to calculate beamforming weights without computationally expensive matrix inversions.
Not ideal if you are not working with advanced wireless communication systems, specifically MU-MIMO beamforming.
Stars
8
Forks
2
Language
Python
License
MIT
Category
Last pushed
Oct 26, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/FenghaoZhu/Matrix-Inverse-Free-WMMSE"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
NVlabs/sionna
Sionna: An Open-Source Library for Research on Communication Systems
lab-emi/OpenDPD
OpenDPD is an end-to-end learning framework built in PyTorch for power amplifier (PA) modeling...
utcsilab/score-based-channels
Source code for paper "MIMO Channel Estimation using Score-Based Generative Models", published...
DeepMIMO/DeepMIMO
DeepMIMOv4: A Toolchain and Database for Ray-tracing Datasets.
NVlabs/neural_rx
Real-Time Inference of 5G NR Multi-user MIMO Neural Receivers