Autoencoder for end-to-end learning communication system based on NOMA
Author:
Affiliation:
1. Amity University,Gwalior,India
2. ABV IIITM,Gwalior,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9997570/9997811/09997900.pdf?arnumber=9997900
Reference19 articles.
1. Adagrad-an optimizer for stochastic gradient descent;agnes;Int J Inf Comput Sci,2019
2. Data-Rate Driven Transmission Strategies for Deep Learning-Based Communication Systems;xiao;IEEE Transactions on Communications,2020
3. Deep Learning Based Power Allocation Schemes in NOMA Systems: A Review
4. An optimization strategy based on hybrid algorithm of Adam and SGD;yijun;MATEC Web of Conferences EDP Sciences,2018
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Improved End-to-End Wireless Transmission Integrating NOMA and DL-Based Autoencoder;IETE Journal of Research;2024-01-21
2. An End-to-End Autoencoder For FSO System Under Unknown CSI Scenarios;2023 21st International Conference on Optical Communications and Networks (ICOCN);2023-07-31
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