Power Control Based on Deep Reinforcement Learning for Spectrum Sharing

• Published in: IEEE transactions on wireless communications Vol. 19; no. 6; pp. 4209 - 4219
• Main Authors: Zhang, Haijun, Yang, Ning, Huangfu, Wei, Long, Keping, Leung, Victor C. M.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Artificial intelligence; Artificial neural networks; Cognitive radio; cognitive radio network; Deep reinforcement learning (DRL); Energy conversion efficiency; Interaction models; Machine learning; Neural networks; Optimization; Power control; Quality of service; Resource management; Sensors; spectrum sharing; Wireless communication; Wireless communications; Wireless networks; Wireless sensor networks

In the current researches, artificial intelligence (AI) plays a crucial role in resource management for the next generation wireless communication network. However, traditional RL cannot solve the continuous and high dimensional problems. To handle these problems, the concept of deep neural network...