Firefly Algorithm for Movable Antenna Arrays

TL;DR

This paper introduces a firefly algorithm to optimize the position and beamforming of movable antenna arrays, improving beamforming gain while controlling interference, outperforming existing methods.

Contribution

It presents a novel swarm-intelligence-based firefly algorithm for joint optimization of antenna position and beamforming vectors in MAAs.

Findings

The proposed FA outperforms state-of-the-art methods in simulation.

It effectively handles non-convex, multimodal optimization problems.

The approach achieves higher minimum beamforming gain with interference constraints.

Abstract

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.