DMA-aided MU-MISO Systems for Power Splitting SWIPT via Lorentzian-Constrained Holography

2025-11-11

AI Summary

This work addresses the transmit power minimization problem in a dynamic metasurface antenna (DMA)-assisted multi-user MISO simultaneous wireless information and power transfer (SWIPT) system, subject to users’ SINR requirements and nonlinear energy harvesting (EH) constraints. To this end, we propose an adaptive-radius Lorentz-constrained holographic (ARLCH) beamforming method that jointly optimizes amplitude and phase responses—enabling efficient beam steering without RF chains or phase shifters. Integrated with an optimal power splitting strategy, we formulate a semidefinite programming-based alternating optimization framework that explicitly accounts for circuit noise. Simulation results demonstrate that the proposed scheme achieves substantial transmit power reduction compared to benchmark methods, validating both the effectiveness of the ARLCH model and the accuracy of the nonlinear EH modeling in DMA-SWIPT systems.

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

This paper presents an optimal power splitting and beamforming design for co-located simultaneous wireless information and power transfer (SWIPT) users in Dynamic Metasurface Antenna (DMA)-aided multiuser multiple-input single-output (MISO) systems. The objective is to minimize transmit power while meeting users signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) requirements. The problem is solved via an alternating optimization framework based on semidefinite programming (SDP), where metasurface tunability follows Lorentzian-constrained holography (LCH). In contrast to traditional beamforming architectures, DMA-assisted architectures reduce the need for RF chains and phase shifters but require optimization under the Lorentzian constraint limiting the amplitude and phase optimizations. Hence, the proposed method integrates several LCH schemes, including the recently proposed adaptive-radius LCH (ARLCH), and evaluates nonlinear EH models and circuit noise effects. Simulation results show that the proposed design significantly reduces transmit power compared with baseline methods, highlighting the efficiency of ARLCH and optimal power splitting in DMA-assisted SWIPT systems.

Problem

• Minimizing transmit power for SWIPT users in DMA-aided MISO systems
• Meeting SINR and energy harvesting requirements simultaneously
• Optimizing power splitting and beamforming under Lorentzian constraints

Innovation

• DMA-aided architecture reduces RF chains and phase shifters
• Alternating optimization with semidefinite programming for beamforming
• Lorentzian-constrained holography schemes optimize amplitude and phase