欢迎提交未收录的代码
yshenaw opened this issue · 65 comments
如果你知道一些相关的开源论文，但不在此列表中，非常欢迎添加在此issue当中，感谢为开源社区贡献一份力量
L. Huang, S. Bi, and Y. J. Zhang, “Deep reinforcement learning for online computation offloading in wireless powered mobile-edge computing networks,” IEEE Trans. Mobile Compt., vol. 19, no. 11, pp. 2581-2593, November 2020.
J. Wang, J.Hu, G. Min, A. Y. Zomaya, and N. Georgalas, “Fast Adaptive Computation Offloading in Edge Computing based on Meta Reinforcement Learning“. IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 1, pp. 242--253, 2021.
建议在表格的每一行前添加序号 方便大家知道最近添加的是哪些论文代码
建议在表格的每一行前添加序号 方便大家知道最近添加的是哪些论文代码
一般最前面的就是新添加的，但是不能保证新添加论文发表的时间也是最新的。
K. Pratik, B. D. Rao, and M. Welling, “RE-MIMO: Recurrent and Permutation Equivariant Neural MIMO Detection,” IEEE Trans. Signal Process., vol. 69, pp. 459–473, 2021.
F. B. Mismar, A. Alammouri, A. Alkhateeb, J. G. Andrews, and B. L. Evans, “Deep Learning Predictive Band Switching in Wireless Networks,” IEEE Transactions on Wireless Communications, vol. 20, no. 1, pp. 96–109, Jan. 2021, doi: 10.1109/TWC.2020.3023397.
H. Chang, H. Song, Y. Yi, J. Zhang, H. He and L. Liu, "Distributive Dynamic Spectrum Access Through Deep Reinforcement Learning: A Reservoir Computing-Based Approach," in IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1938-1948, April 2019, doi: 10.1109/JIOT.2018.2872441.
https://ieeexplore.ieee.org/document/8474348
https://github.com/haohsuan2918/DQN_RC_DSA_IOT2019
Suzhi Bi, Liang Huang, Hui Wang, and Ying-Jun Angela Zhang, "Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks," IEEE Transactions on Wireless Communications, 2021, doi:10.1109/TWC.2021.3085319.
https://ieeexplore.ieee.org/document/9449944
https://github.com/revenol/LyDROO
H. He, C. Wen, S. Jin, and G. Y. Li, “Model-driven deep learning for MIMO detection,” IEEE Trans. Signal Process., vol. 68, pp. 1702–1715, Feb. 2020.
https://ieeexplore.ieee.org/document/9018199/
https://github.com/hehengtao/OAMP-Net
J. Choi, Y. Cho, B. L. Evans and A. Gatherer, "Robust Learning-Based ML Detection for Massive MIMO Systems with One-Bit Quantized Signals," 2019 IEEE Global Communications Conference (GLOBECOM), 2019, pp. 1-6, doi: 10.1109/GLOBECOM38437.2019.9013332.
Lee M, Yu G, Li G Y. Graph Embedding-Based Wireless Link Scheduling With Few Training Samples[J]. IEEE Transactions on Wireless Communications, 2020, 20(4): 2282-2294.
https://github.com/mengyuan-lee/graph_embedding_link_scheduling
Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas Donald Lane, and Timothy Hospedales. "A Channel Coding Benchmark for Meta-Learning." NeurIPS 2021 Datasets and Benchmarks Track
https://openreview.net/forum?id=DjzPaX8AT0z
https://github.com/ruihuili/MetaCC
J. Wang, J.Hu, G. Min, W. Zhan, A. Y. Zomaya, and N. Georgalas, "Dependent Task Offloading for Edge Computing based on Deep Reinforcement Learning." IEEE Transactions on Computers, 2021.
https://ieeexplore.ieee.org/abstract/document/9627763
https://github.com/linkpark/RLTaskOffloading
Q. Hu, Y. Liu, Y. Cai, G. Yu, and Z. Ding, “Joint deep reinforcement learning and unfolding: Beam selection and precoding for
mmWave multiuser MIMO with lens arrays,” IEEE J. Sel. Areas Commun., vol. 39, no. 8, pp. 2289–2304, Jun. 2021.
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9448095
https://github.com/hqyyqh888/DDQN_BeamSelection
S. Wang, S. Bi and Y. -J. A. Zhang, "Deep Reinforcement Learning with Communication Transformer for Adaptive Live Streaming in Wireless Edge Networks," in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2021.3126062.
https://ieeexplore.ieee.org/document/9605672
https://github.com/wsyCUHK/SACCT
H. Lu, M. Jiang and J. Cheng, "Deep Learning Aided Robust Joint Channel Classification, Channel Estimation, and Signal Detection for Underwater Optical Communication," in IEEE Transactions on Communications, vol. 69, no. 4, pp. 2290-2303, April 2021, doi: 10.1109/TCOMM.2020.3046659.
https://ieeexplore.ieee.org/document/9302692
https://github.com/Huaiyin-Lu/UWOC-JCCESD
Z. He, L. Wang, H. Ye, G. Y. Li and B. -H. F. Juang, "Resource Allocation based on Graph Neural Networks in Vehicular Communications," GLOBECOM 2020 - 2020 IEEE Global Communications Conference, 2020, pp. 1-5, doi: 10.1109/GLOBECOM42002.2020.9322537.
https://github.com/Coolzyh/Globecom2020-ResourceAllocationGNN
群人数超过200，进不去了。
Wang, J., Hu, J., Min, G., Ni, Q., & El-Ghazawi, T. (2022). Online Service Migration in Mobile Edge with Incomplete System Information: A Deep Recurrent Actor-Critic Learning Approach. IEEE Transactions on Mobile Computing.
https://ieeexplore.ieee.org/document/9853218
https://github.com/linkpark/pomdp-service-migration
L. Zhang, J. Tan, Y. -C. Liang, G. Feng and D. Niyato, "Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks," in IEEE Transactions on Wireless Communications, vol. 18, no. 6, pp. 3281-3294, June 2019, doi: 10.1109/TWC.2019.2912754.
F. Saggese, L. Pasqualini, M. Moretti and A. Abrardo, "Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic," 2021 IEEE Global Communications Conference (GLOBECOM), 2021, pp. 1-6, doi: 10.1109/GLOBECOM46510.2021.9685777.
L. Pasqualini and F. Saggese, "Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic", GitHub repository, 2021, [online] Available: https://github.com/InsaneMonster/telerl2021.
Zhongyuan Zhao, Ananthram Swami, Santiago Segarra, Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems, ICLR 2023
https://openreview.net/pdf?id=yHIIM9BgOo
https://github.com/XzrTGMu/twin-nphard
这篇最新收录于ICLR2023的文章提出一种通用的强化学习架构，用以解决重复性的组合优化问题，尤其是适合需要快速、或者分布式方案的应用。文中演示了4种不同的NP-hard组合优化问题,MWIS, MWDS, NWST, MWCDS，这几个问题常见于通信网络的调度和路由等资源分配任务中。
S. Wang, S. Bi and Y. -J. A. Zhang, "Edge Video Analytics with Adaptive Information Gathering: A Deep Reinforcement Learning Approach," in IEEE Transactions on Wireless Communications, doi: 10.1109/TWC.2023.3237202. https://ieeexplore.ieee.org/document/10025689
https://github.com/wsyCUHK/DBAG
Z. Ren, N. Cheng, R. Sun, X. Wang, N. Lu and W. Xu, "SigT: An Efficient End-to-End MIMO-OFDM Receiver Framework Based on Transformer," 2022 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA), Cairo, Egypt, 2022, pp. 1-6, doi: 10.1109/ICCSPA55860.2022.10019001.
S. Wang, J. Yang and S. Bi, "Adaptive Video Streaming in Multi-Tier Computing Networks: Joint Edge Transcoding and Client Enhancement," in IEEE Transactions on Mobile Computing, doi: 10.1109/TMC.2023.3263046. https://ieeexplore.ieee.org/document/10089145
您好。最近我在研究利用强化学习解决双能源供电的通信网络中资源优化问题，但发现几乎没有近几年开源的代码。请问大家有知道的吗？谢谢！
Paper : "Meta-ViterbiNet: Online Meta-Learned Viterbi Equalization for Non-Stationary Channels"
https://arxiv.org/abs/2103.13483
Code : https://github.com/tomerraviv95/meta-viterbinet?tab=readme-ov-file