Research on Distributed Dynamic Spectrum Access Based on Deep Reinforcement Learning
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7505-1_20
Reference13 articles.
1. Carie A, Li M, Marapelli B et al (2019) Cognitive radio assisted WSN with interference aware AODV routing protocol. J Ambient Intell Humaniz Comput 10:4033–4042
2. Song H, Liu L, Ashdown J et al (2021) A deep reinforcement learning framework for spectrum management in dynamic spectrum access. IEEE Internet Things J 8(14):11208–11218
3. Cai P, Zhang Y (2020) Intelligent cognitive spectrum collaboration: Convergence of spectrum sensing, spectrum access, and coding technology. Intelligent and Converged Networks 1(1):79–98
4. Qian B, Zhou H, Ma T et al (2020) Leveraging dynamic stackelberg pricing game for multi-mode spectrum sharing in 5G-VANET. IEEE Trans Veh Technol 69(6):6374–6387
5. Liu X, Sun C, Yu W et al (2021) Reinforcement-Learning-based dynamic spectrum access for software-defined cognitive industrial internet of things. IEEE Trans Industr Inf 18(6):4244–4253
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