Spatially Robust Near-Field SWIPT Using Pinching Antennas: Rate-Energy Tradeoff Bounds

2026-06-18

AI Summary

This work addresses the sensitivity of conventional point-to-point optimization in near-field simultaneous wireless information and power transfer (SWIPT) to user location errors and mobility, which undermines service reliability over a coverage area. To enhance robustness against user displacement, the paper proposes a service-area-oriented discrete antenna selection framework that jointly satisfies quality-of-service requirements in both information decoding and energy harvesting regions through optimized antenna activation patterns. A novel theoretical framework characterizing the rate-energy tradeoff is established by deriving tight upper and lower bounds: the upper bound is obtained via semidefinite relaxation of a non-convex binary quadratic program, while the lower bound is achieved by a low-complexity swap-based local search algorithm under practical hardware constraints. Experimental results demonstrate that the proposed scheme delivers stable and superior rate-energy tradeoff performance across the service area compared to existing point-to-point approaches.

Abstract

Pinching Waveguide Antennas (PWAs) offer significant potential for simultaneous wireless information and power transfer (SWIPT) by enabling precise near-field energy focusing. However, existing optimization frameworks are largely point-based (targeting a single coordinate for maximum gain), and thus highly sensitive to positioning errors and mobility, as near-field signals fluctuate significantly even over small spatial displacements. In this paper, we propose a spatially robust design framework based on discrete antenna selection optimized for service area (SA) coverage. Unlike point-based approaches, our model guarantees quality of service within predefined SAs for both information decoding (ID) and energy harvesting (EH) receivers, thereby improving robustness to user displacements. We formulate the problem as a non-convex binary quadratic program aimed at maximizing harvested energy within the EH SA subject to robust rate constraints in the ID SA. To characterize fundamental performance limits, we develop a semidefinite relaxation (SDR) framework that provides an upper bound on the achievable rate-energy (R-E) region. For the lower bound, we employ a low-complexity swap-based local search algorithm enforcing binary hardware constraints. Numerical results demonstrate that the proposed coverage-oriented design yields a robust R-E tradeoff and maintains stable performance across service regions, highlighting the advantages of discrete antenna activation over point-based near-field optimization approaches.

Problem

• SWIPT
• near-field
• spatial robustness
• rate-energy tradeoff
• positioning sensitivity

Innovation

• Spatially Robust SWIPT
• Pinching Waveguide Antennas
• Service Area Coverage
• Rate-Energy Tradeoff
• Discrete Antenna Selection