Beamforming Optimization for Continuous Aperture Array (CAPA)-based Communications
Zhaolin Wang, Chongjun Ouyang, Yuanwei Liu

TL;DR
This paper introduces low-complexity beamforming optimization methods for continuous aperture arrays in multi-user communications, significantly improving performance and reducing computational complexity over traditional discretization techniques.
Contribution
It proposes two novel approaches, CoV-based and Corr-ZF, for optimizing beamforming in CAPA systems, addressing the non-convex integral problem efficiently.
Findings
CoV-based approach reduces complexity by up to hundreds of times.
Corr-ZF achieves asymptotically optimal performance.
Proposed methods outperform Fourier-based discretization.
Abstract
The beamforming optimization in continuous aperture array (CAPA)-based multi-user communications is studied. In contrast to conventional spatially discrete antenna arrays, CAPAs can exploit the full spatial degrees of freedom (DoFs) by emitting information-bearing electromagnetic (EM) waves through continuous source current distributed across the aperture. Nevertheless, such an operation renders the beamforming optimization problem as a non-convex integral-based functional programming problem, which is challenging for conventional discrete optimization methods. A couple of low-complexity approaches are proposed to solve the functional programming problem. 1) Calculus of variations (CoV)-based approach: Closed-form structure of the optimal continuous source patterns are derived based on CoV, inspiring a low-complexity integral-free iterative algorithm for solving the functional…
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Taxonomy
TopicsAntenna Design and Optimization · Antenna Design and Analysis · Radio Astronomy Observations and Technology
