Run train.py for BSC or AWGN channel
Run train_OFDM.py for multipath channel based on OFDM system
So far, can only work with CIFAR-10 dataset. Currently working to include CelebA
Three GANs available: vanilla GAN, LSGAN, WGAN
BSC channel:
- Soft and hard Gunbel Softmax relaxed Bernoulli distribution
OFDM system:
- LS, LMMSE channel estimation
- ZF, MMSE, implicit equalization
- A version of feedback of CSI included
- ssh port forwarding from server to local machine
ssh -N -f -L localhost:8998:localhost:8998 username@server
- Then view the training dynamics in
localhost:8998
with local browser
Use nohup to run multiple threads
The basic coding framework is based on pix2pix Github
- Support multiple pilots for channel estimation
- Added three forward methods
- Able to test the OFDM channel in models/test_OFDM.py
- Fixed a bug in OFDM system
- Modified the clipping layer
- Modified LLR calculation for baseline
- Added QPSK symbols as pilots
- Added scripts to train pure GAN
- Add residual connections
- Two kinds of pilots (QPSK, ZadoffChu)
- New LLR calculation for baseline clipping