基于混合用户的认知无线电网络中的模式识别无线电资源分配算法
1Centre for Advanced Spatial Analysis, University College London, Gower Street, London WC1E 6BT, UK.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
这项研究引入了一种使用混合用户的新型认知无线电网络算法,以提高频道利用率和效率. 这种新方法提高了二级用户的性能,同时保持了主要用户的质量和网络的能源效率.
科学领域:
- 无线通信网络
- 资源分配的优化
- 认知无线电技术
背景情况:
- 认知无线电网络 (CRN) 优先考虑主要用户 (PU),限制次要用户 (SUs).
- 传统的资源分配方式造成浪费,缺乏适应性.
- 在CRN中强化学习要求高计算能力,阻碍了工业使用.
研究的目的:
- 提出一个有效的CRN算法,解决现有方法的局限性.
- 提高道资源利用率和网络性能.
- 提高工业CRN部署的适应性和可扩展性.
主要方法:
- 引入了混合用户 (HU) 概念,将交织和底层模式与自适应切换联系起来.
- 采用匈牙利的方法进行 SU 频道分配.
- 应用了多层次的功率调整策略.
主要成果:
- 改善了SUS的平均信号与干扰加噪声比 (SINR).
- 确保主要用户 (PU) 的服务质量.
- 显著提高了网络能源效率,
结论:
- 拟议的基于HU的CRN算法提供了一个可扩展和高效的解决方案.
- 它优化了资源分配,提高了SU的性能和网络效率.
- 该算法在工业CRN应用中表现出卓越的适应性.
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