项目说明

Simulation code for "End-to-End Supervised Learning for NOMA-enabled Resource Allocation: a Dynamic and Scalable Approach"

pip install -r requirements.txt

step 1 Generate data

python DataOperation.py 

step 2 Train model

using PTN

python SLPTN.py

using GPN

python SLGPN.py

execute in the background

nohup python SLGPN.py > slgpn.log &
nohup python SLPTN.py > slptn.log &

results

tail -f nohup.out