活动检测和道估计基于相关的混合消息传递,免费提供大规模随机访问
Xiaofeng Liu1, Xinrui Gong2, Xiao Fu2,3
1School of Artificial Intelligence, Yancheng Teachers University, Yancheng 224000, China.
Entropy (Basel, Switzerland)
|November 26, 2025
概括
未来的6G网络需要精确的活跃用户检测和通道估计 (AUDCE) 进行大规模的机器类型通信. 一个新的相关混合消息传递算法有效地解决了无补贴访问系统中的这一挑战.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 信息理论 信息理论
背景情况:
- 未来的6G网络将支持大量的机器类型通信 (mMTC),具有众多设备和零星流量.
- 免费访问对于减少mMTC中的延迟和开销至关重要,需要准确的活跃用户检测和通道估计 (AUDCE).
研究的目的:
- 在宽带大规模访问系统中调查联合AUDCE问题.
- 为准确的AUDCE开发一个创新的道先验模型和一个高效的算法.
主要方法:
- 开发了一种使用马尔科夫链和合高斯分布的新通道前模型,以捕捉双通道相关性.
- 提出了基于Bethe自由能量最小化的相关混合信息传递 (CHMP) 算法.
- 该CHMP算法适应地更新参数,而无需事先了解用户稀疏性或道特征.
主要成果:
- 拟议的道先导模型有效地描述了结构和数值道依赖.
- 人类药物管理委员会 (CHMP) 的算法证明了准确的活跃用户检测.
- 在模拟中使用CHMP算法实现了精确的通道估计.
结论:
- 在宽带大规模访问系统中,CHMP算法为联合AUDCE提供了有效的解决方案.
- 开发的道先前模型增强了对mMTC道结构的理解.
- 这项工作有助于推进高效可靠的6G通信系统.
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