Soft Robotics-Inspired Flexible Antenna Arrays

TL;DR

This paper introduces a soft robotics-inspired flexible antenna array that can reconfigure its geometry to optimize network performance, outperforming traditional fixed and reconfigurable arrays.

Contribution

It presents a novel deformable antenna array inspired by soft robotics, with a new optimization approach for maximizing network sum rate.

Findings

Deformable array outperforms fixed and reconfigurable arrays in sum rate.

Continuous deformation improves antenna array performance.

Optimization method effectively finds optimal deformation parameters.

Abstract

In this work, a novel soft continuum robot-inspired antenna array is proposed, featuring tentacle-like structures with multiple antenna elements. The proposed array achieves reconfigurability through continuous deformation of its geometry, in contrast to reconfigurable antennas which incur a per-element control. More specifically, the deformation is modeled by amplitude and spatial frequency parameters. We consider a multi-user multiple-input single-output downlink system, whereby the optimal deformation parameters are found to maximize the sum rate in the network. A successive convex approximation method is adopted to solve the problem. Numerical results show that the proposed deformable array significantly outperforms fixed geometry and per-element reconfigurable arrays in sum rate, demonstrating the benefits of structure-level flexibility for next-generation antenna arrays.