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Paper-with-Code-of-Wireless-communication-Based-on-DL is a curated repository that collects research papers and corresponding code implementations related to the application of deep learning in wireless communication systems. The project aims to help researchers and graduate students quickly find reproducible implementations of algorithms used in modern communication research. Wireless communication research has increasingly adopted deep learning techniques to address complex tasks such as channel estimation, resource allocation, signal detection, and modulation classification. However, many academic publications do not release source code, which makes it difficult for new researchers to reproduce results or experiment with the proposed methods. This repository addresses that challenge by organizing a large set of papers and linking them to available implementations and related research resources.
Features
- Curated list of research papers applying deep learning to wireless communication
- Links between academic publications and open-source code implementations
- Coverage of topics such as channel estimation, modulation recognition, and resource allocation
- Organization of research materials into communication system subfields
- Continuous updates through community contributions and pull requests
- Educational resource for researchers entering deep learning-based communication research
Project Samples
