This repository includes the source code of the DL-based symbol-by-symbol (SBS) and frame-by-frame (FBF) 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.
- FNN-based channel estimators: https://github.com/abdulkarimgizzini/Deep-Learning-Based-Channel-Estimation-Schemes-for-IEEE-802.11p-Standard
- LSTM-based channel estimators: https://github.com/abdulkarimgizzini/Temporal-Averaging-LSTM-based-Channel-Estimation-Scheme-for-IEEE-802.11p-Standard
- DFT-based channel estimators: https://github.com/abdulkarimgizzini/Low-Complex-Methods-for-Robust-Channel-Estimation-in-Doubly-Dispersive-Environments
- CNN-based channel estimators: https://github.com/abdulkarimgizzini/CNN-Aided-Weighted-Interpolation-for-Channel-Estimation-in-Vehicular-Communications
For more information and questions, please contact me on abdulkarimgizzini@gmail.com