Source codes of the article: P. Dong, H. Zhang and G. Y. Li, "Framework on Deep Learning-Based Joint Hybrid Processing for mmWave Massive MIMO Systems," IEEE Access, vol. 8, pp. 106023-106035, 2020. Please cite this paper when using the codes.
This folder contains codes for channel data generation executed in MATLAB and codes for channel estimation executed in Python.
-
Narrow band
(1) Use MIMO_3GPP_channel_multi_fre.m to generate channel data for training and testing
(2) Use DL_JHPF_train.py to train DL-JHPF and save model.
(2) Use DL_JHPF_train_further.py to further train DL-JHPF based on the saved model.
(3) Use DL_JHPF_test.py to test the performance of the trained DL-JHPF.
-
OFDM
(1) Use MIMO_3GPP_channel_multi_fre.m to generate channel data for training and testing
(2) Use DL_JHPF_ofdm_train.py to train DL-JHPF and save model.
(2) Use DL_JHPF_ofdm_train_further.py to further train DL-JHPF based on the saved model.
(3) Use DL_JHPF_ofdm_test.py to test the performance of the trained DL-JHPF.