Low-complexity Design for Beam Coverage in Near-field and Far-field: A Fourier Transform Approach
Chao Zhou, Changsheng You, Cong Zhou, Li Chen, Yi Gong, and Chengwen Xing

TL;DR
This paper introduces a low-complexity Fourier transform-based method for designing beam coverage in multi-antenna systems, effectively handling both near-field and far-field scenarios with reduced computational effort.
Contribution
It proposes a novel FT-based beam coverage design framework that addresses roll-off effects and extends to near-field cases, improving efficiency over traditional sampling methods.
Findings
Achieves comparable worst-case beamforming gain to existing methods.
Reduces computational complexity significantly.
Provides effective beam coverage in both near-field and far-field scenarios.
Abstract
In this paper, we study efficient beam coverage design for multi-antenna systems in both far-field and near-field cases. To reduce the computational complexity of existing sampling-based optimization methods, we propose a new low-complexity yet efficient beam coverage design. To this end, we first formulate a general beam coverage optimization problem to maximize the worst-case beamforming gain over a target region. For the far-field case, we show that the beam coverage design can be viewed as a spatial-frequency filtering problem, where angular coverage can be achieved by weight-shaping in the antenna domain via an inverse FT, yielding an infinite-length weighting sequence. Under the constraint of a finite number of antennas, a surrogate scheme is proposed by directly truncating this sequence, which inevitably introduces a roll-off effect at the angular boundaries, yielding degraded…
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Taxonomy
TopicsAntenna Design and Optimization · Direction-of-Arrival Estimation Techniques · Advanced MIMO Systems Optimization
