Multi-User Opportunistic Spectrum Access for Cognitive Radio Networks Based on Multi-Head Self-Attention and Multi-Agent Deep Reinforcement Learning

Aiming to address the issue of multi-user dynamic spectrum access in an opportunistic mode in cognitive radio networks leading to low sum throughput, we propose a multi-user opportunistic spectrum access method based on multi-head self-attention and multi-agent deep reinforcement learning. First, an...

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Bibliographic Details
Main Authors:	Weiwei Bai, Guoqiang Zheng, Weibing Xia, Yu Mu, Yujun Xue
Format:	Article
Language:	English
Published:	MDPI AG 2025-03-01
Series:	Sensors
Subjects:	opportunistic spectrum access throughput multi-head self-attention multi-agent deep reinforcement learning multi-user spectrum access cognitive radio network
Online Access:	https://www.mdpi.com/1424-8220/25/7/2025
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Multi-User Opportunistic Spectrum Access for Cognitive Radio Networks Based on Multi-Head Self-Attention and Multi-Agent Deep Reinforcement Learning

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