Watch zhoub86/DNN_WMMSE

Code to reproduce our works on DNN research.

Watch zhoub86/entropy

Entropy estimator

Watch zhoub86/pg-ofdm-distortion

UFES-PG: Harmonic distortion in OFDM signals for IM-DD systems

Watch zhoub86/AutoEncoder-Based-Communication-System

Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

Watch zhoub86/Optical-Comm-ML

Machine learning for optical communication over a dispersive fiber

Watch zhoub86/ML-in-physical-layer

Watch zhoub86/FBMC

Compares FBMC to OFDM based schemes. Reproduces all figures from “Filter bank multicarrier modulation schemes for future mobile communications”, IEEE Journal on Selected Areas in Communications, 2017.

Watch zhoub86/Iterative-BP-CNN

The codes reproduce the research of our work in our JSTSP paper "An Iterative BP-CNN Architecture for Channel Decoding under Correlated Noise"

Watch zhoub86/DensityEstimationML.jl

A neural network based method for estimation continuous conditional distributions

Watch zhoub86/ECE257B_OFDM_NL

ECE257B (Sp2018) : Reception of Nonlinearly Distorted Multicarrier Signals