与深度神经网络一起进行主动和被动建模,作为上中频段6G通信的全自动化优化
Lida Kouhalvandi1, Ladislau Matekovits2,3,4
1Department of Electrical and Electronics Engineering, Dogus University, Istanbul, 34775, Turkey.
Scientific reports
|August 3, 2024
概括
本研究介绍了一种用于设计6G无线系统的高性能射频放大器和天线的自动化方法. 该方法使用深度神经网络和多目标优化,同时设计主动和被动组件,缩短上市时间.
科学领域:
- 电气工程 电气工程
- 无线通信无线通信
- 电磁学 电磁学 电磁学 电磁学
背景情况:
- 第五代和第六代 (5G/6G) 无线系统面临着指数级增长的数据流量,需要高性能射频 (RF) 组件.
- 5G/6G需求放大器中的传播损失具有高输出功率和天线,用于管理信号并补偿射频电路非线性.
- 对于射频设计人员来说,积极 (放大器) 和被动 (天线) 组件的同时优化是一个挑战.
研究的目的:
- 为6G无线系统提供高性能放大器和天线的全面设计和优化提出两步自动化方法.
- 为了解决同时优化主动和被动射频组件的复杂性.
- 为了缩短先进的射频设计的上市时间.
主要方法:
- 一种两步方法,涉及初始设备结构配置和随后的设备尺寸.
- 利用人工智能,特别是基于长期短期记忆 (LSTM) 的深度神经网络 (DNN),用于替代模型和自动优化.
- 在DNN输出层使用多目标多层优化器 (MOMVO) 来同时优化放大器和天线规格.
- 整合电磁 (EM) 设计规则以最大限度地减少模拟时间并生成准备制造的布局.
主要成果:
- 使用自下向上优化 (BUO) 方法和基于LSTM的DNN的天线的高性能放大器的综合设计的自动化优化过程.
- 使用MOMVO方法,成功地同时优化了主动 (放大器) 和被动 (天线) 设备.
- 由于实施了EM设计规则,在平衡模拟环境中减少了模拟时间.
- 生产出具有全球最佳性能的现成布局.
结论:
- 拟议的全包式设计风格显著减少了RF元件的手动干预和上市时间.
- 自动化方法提供全球优化的,高性能放大器和天线的准备制造设计.
- 该方法通过设计和优化一台高功率放大器 (HPA) 与用于上中频段6G通信 (9.09.6 GHz) 的天线进行验证.
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