A Joint Scheme on Spectrum Sensing and Access with Partial Observation: A Multi-Agent Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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A Joint Scheme on Spectrum Sensing and Access with Partial Observation: A Multi-Agent Deep Reinforcement Learning Approach

Published:2023-08-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CIC International Conference on Communications in China (ICCC)
language:
Short-container-title:

Author:

Zhang Yulong¹,Li Xuanheng¹,Ding Haichuan²,Fang Yuguang³

Affiliation:

1. Dalian University of Technology,School of Information and Communication Engineering,Dalian,China

2. Beijing Institute of Technology,School of Cyberspace Science and Technology,Beijing,China

3. City University of Hong Kong,Department of Computer Science,Hong Kong,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10233255/10233122/10233366.pdf?arnumber=10233366

Reference22 articles.

1. Enhanced Dynamic Spectrum Access in Multiband Cognitive Radio Networks via Optimized Resource Allocation

2. Cooperative Spectrum Sensing Optimization in Energy-Harvesting Cognitive Radio Networks

3. Deep Reinforcement Learning for Dynamic Spectrum Sensing and Aggregation in Multi-Channel Wireless Networks

4. Distributed and Secure Uplink Power Control in Dynamic Spectrum Access

5. Deep Reinforcement Learning for Simultaneous Sensing and Channel Access in Cognitive Networks

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