Paper-with-Code-of-Wireless-communication-Based-on-DL
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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.
https://github.com/revenol/DROO
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.
https://arxiv.org/abs/2008.02033
https://github.com/linkpark/metarl-offloading
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.
https://arxiv.org/abs/2007.00140
https://github.com/krpratik/RE-MIMO
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.
https://ieeexplore.ieee.org/abstract/document/9199558
https://github.com/farismismar/Bandswitch-DeepMIMO
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
https://mlc.committees.comsoc.org/papers-with-code/
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.
https://github.com/Yunseong-Cho/LearningML
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
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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
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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
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群人数超过200,进不去了。
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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
邮件已经收到,谢谢,祝好~!
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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.
url:https://ieeexplore.ieee.org/document/8703432