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chenmingzhe 84091a1a9f | 3 years ago | |
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models | 3 years ago | |
utils | 3 years ago | |
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README.md | 3 years ago | |
main_fed.py | 3 years ago |
This is the source code for implementing the paper of "One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis" (published at IEEE Transactions on Wireless Communications). In this paper, we proposed to integrate communication and computation in a joint design to reduce the multi-access latency during the model uploading and aggregation in federated edge learning
Two experiments in the paper are included:
CNN on MNIST dataset
ResNet18 on CIFAR10 dataset
python = 3.6.5
pytorch = 1.0.0
CUDA_VISIBLE_DEVICES=0 python main_fed.py --dataset mnist --iid --num_channels 1 --model cnn --num_users 100 --epochs 300 --lr 0.0001 --frac 1.0 --local_ep 1 --momentum 0.0 --local_bs 50 --bs 50
CUDA_VISIBLE_DEVICES=2 python main_fed.py --dataset cifar --iid --num_channels 3 --model resnet18 --num_users 100 --snr 10 --epochs 300 --lr 0.001 --frac 1.0 --local_ep 1 --momentum 0.0 --local_bs 512 --bs 512 --lr-scheduler --mode NP_CSI --thd 2.8 --delta 0.01
The output of the experiment is a .log file including all the training results, e.g. training loss and test accuracy;
The configurable parameters in the code are defined in the file "option.py".
Net4AI 是未来(6G)内生智慧网络的两大技术发展方向之一,该方向的研究目标为充分利用网络节点的通信、计算和感知能力,通过分布式学习、群智式协同以及云边端一体化算法部署,支撑更为强大的网络智能(Network Intelligence),以实现未来各种智慧应用。本项目将对Net4AI相关论文的实现代码进行汇总,方便相关论文结果的复现,以促进该领域的健康发展。
Unity3D Asset CSV Text Python MATLAB other
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