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层次MAB框架用于能源意识束训练,用于近场通信

Yunxing Xiang¹, Yi Yan¹, Yunchao Song²

¹Supply Service Management Center, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330001, China.

Sensors (Basel, Switzerland)

|January 10, 2026

概括

本研究介绍了使用多臂盗 (MAB) 框架对XL-MIMO系统的节能束训练方法. 它优化了用户的调度和光束选择,以改善通信质量并延长设备的电池寿命.

科学领域:

无线通信无线通信
信号处理信号处理
电信工程电信工程电信工程

背景情况:

对于多用户通信,XL-MIMO系统需要高效的光束训练.
将通信质量与设备能源效率相平衡,对于系统的寿命至关重要.

研究的目的:

为XL-MIMO多用户频率分割双重系统提出一个新的近场光束训练方案.
通过整合能源意识的用户调度和层次束训练来提高系统的能源效率和延长设备寿命.

主要方法:

使用的是一个双相组合的多武装强盗 (MAB) 框架.
一个具有能源意识的上置信限 (UCB) 算法被设计用于用户调度,优先考虑具有高速率和充足电池的用户.
层次束训练采用了两个UCB算法:一个用于使用DFT代码簿进行初始角度采集,另一个用于最佳的极域代码单词选择.

主要成果:

模拟证实了拟议方案的有效性.
显著的可实现速率增长被证明是多用户通信.
该计划成功地平衡了通信质量和设备电池水平.

结论:

拟议的基于MAB的光束训练方案显著提高了XL-MIMO系统的能源效率.
集成能源意识调度和层次束训练可以提高系统性能和设备寿命.
这种方法为优化未来的无线通信系统提供了可行的解决方案.

关键词:

在KL-UCB上.在MAB中,MAB是MAB,MAB是MAB 在XL-MIMO中使用.射线培训射线培训射线培训能源效率是指能效的能源效率.用户调度使用者调度

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