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人工智能原生PHY层在6G编排的频谱意识网络中

Partemie-Marian Mutescu1, Adrian-Ioan Petrariu1, Eugen Coca1

  • 1Faculty of Electrical Engineering and Computer Science, Ștefan Cel Mare University of Suceava, 720229 Suceava, Romania.

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概括

本研究介绍了6G网络的AI原生PHY层意识,使波形和数值检测直接从无线电信号. 这推动了自我优化和自适应式无线系统的发展.

关键词:
6G网络中的6G网络.B5G 是一个B5G.人工智能的人工智能是人工智能.频谱传感传感器是什么?

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科学领域:

  • 电信工程 电信工程 电信工程
  • 人工智能的人工智能
  • 信号处理 信号处理

背景情况:

  • 过渡到6G无线网络需要在无线接入网络 (RAN) 中向人工智能原生编排迈进.
  • 目前的系统通常依赖于更高层的信号来识别网络参数,这可能是低效的.

研究的目的:

  • 在6G网络中开发基于人工智能的实现器,用于物理 (PHY) 层意识.
  • 在RAN中实现内在智能,以提高频谱意识和系统适应性.

主要方法:

  • 基于AI的波形分类器的开发,以区分直角频率分割多重复合 (OFDM) 和直角时间频率空间 (OTFS) 信号,使用相位/方位 (IQ) 样本.
  • 实现基于人工智能的数字学探测器,以确定诸如子载波间距,FFT大小,槽持续时间和循环前类型等参数,而无需更高层信息.

主要成果:

  • 波形分类实现了99.5%的准确性.
  • 数学检测在大多数参数上都超过了99%的准确性.
  • 证明了波形和数字学特征的强有力的联合推断,证实了AI原生频谱意识的可行性.

结论:

  • 对于6G无线系统来说,人工智能原生PHY层意识是可行的.
  • 开发的启用器为自我优化,上下文意识和自适应性6G网络铺平了道路.
  • RAN中的内在智能增强了频谱利用和系统性能.