Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications

IEEE Transactions on Wireless Communications, 2022

Recommended citation: Fanglei Sun, Yang Li, Ying Wen, Jingchen Hu, Jun Wang, Yang Yang, and Kai Li. "Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications." IEEE Transactions on Wireless Communications 21, no. 8 (2022): 6167-6179. https://ieeexplore.ieee.org/abstract/document/9705656

(ChatGPT-Generated) The paper proposes a novel multi-agent feedback enabled neural network (MAFENN) framework for intelligent communications, which consists of three fully cooperative intelligent agents that have stronger feedback learning capabilities and more intelligence on feature abstraction, denoising or generation. The MAFENN framework is theoretically formulated into a three-player Feedback Stackelberg game and is shown to outperform traditional or DL-based equalizers in wireless fading channels with inter-symbol interference (ISI), demonstrating its effectiveness and robustness in complex channel environments.

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Recommended citation: Fanglei Sun, Yang Li, Ying Wen, Jingchen Hu, Jun Wang, Yang Yang, and Kai Li. “Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications.” IEEE Transactions on Wireless Communications 21, no. 8 (2022): 6167-6179.