基于GA-PSO算法和模糊性函数的2D子数组的稀疏天线阵列的优化设计
Jian Yang1, Jian Lu2, Tong Zhu1
1School of Engineering, Rocket Force University of Engineering, Xi'an 710025, China.
Micromachines
|September 27, 2025
概括
本研究介绍了全相多输入多输出 (FPMIMO) 系统中稀疏天线阵列的最佳设计. 这种新的方法使用混合基因算法-粒子群优化 (GA-PSO) 和模两可的函数来实现高效的数组设计.
科学领域:
- 电气工程 电气工程
- 信号处理 信号处理
- 天线理论天线理论
背景情况:
- 稀少的天线阵列可以降低复杂性和成本,同时提高光圈.
- 全相多输入多输出 (FPMIMO) 系统从高效的阵列配置中受益.
研究的目的:
- 在FPMIMO操作中为稀疏天线阵列提出一个新的最佳设计.
- 为了提高全球优化性能,并适应性地调整代.
主要方法:
- 使用混合基因算法-粒子群集优化 (GA-PSO).
- 结合对最终数组确定的一致性函数.
- 优化代的自适应性调整.
主要成果:
- 在优化稀疏天线阵列方面,拟议的GA-PSO算法的有效性得到证明.
- 成功集成模糊函数,用于精确的数组配置.
- 通过模拟测试验证算法的有效性.
结论:
- 拟议的GA-PSO算法为设计FPMIMO系统中稀疏天线阵列提供了一种有效的方法.
- 适应代调整确保了强大的全球优化.
- 这种设计有助于降低系统复杂性和硬件成本.
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