当前位置: X-MOL 学术IEEE Wirel. Commun. Lett. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Firefly Algorithm for Movable Antenna Arrays
IEEE Wireless Communications Letters ( IF 4.6 ) Pub Date : 2024-09-10 , DOI: 10.1109/lwc.2024.3456899
Manh Kha Hoang 1 , Tuan Anh Le 2 , Kieu-Xuan Thuc 1 , Tong Van Luyen 1 , Xin-She Yang 2 , Derrick Wing Kwan Ng 3
Affiliation  

This letter addresses a multivariate optimization problem for linear movable antenna arrays (MAAs). Particularly, the position and beamforming vectors of the under-investigated MAA are optimized simultaneously to maximize the minimum beamforming gain across several intended directions, while ensuring interference levels at various unintended directions remain below specified thresholds. To this end, a swarm-intelligence-based firefly algorithm (FA) is introduced to acquire an effective solution to the optimization problem. Simulation results reveal the superior performance of the proposed FA approach compared to the state-of-the-art approach employing alternating optimization and successive convex approximation. This is attributed to the FA’s effectiveness in handling non-convex multivariate and multimodal optimization problems without resorting approximations.

中文翻译:


用于可移动天线阵列的 Firefly 算法



这封信解决了线性可移动天线阵列 (MAA) 的多元优化问题。特别是,正在研究的 MAA 的位置和波束赋形矢量同时进行优化,以最大限度地提高多个预期方向的最小波束赋形增益,同时确保各种非预期方向的干扰水平保持在规定的阈值以下。为此,引入一种基于群体智能的萤火虫算法 (FA) 来获得优化问题的有效解决方案。仿真结果表明,与采用交替优化和连续凸近似的最先进的方法相比,所提出的 FA 方法具有卓越的性能。这归因于 FA 在处理非凸多变量和多模态优化问题方面的有效性,而无需使用近似值。
更新日期:2024-09-10
down
wechat
bug