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arxiv: 2510.27185 · v3 · pith:IY2FIAWAnew · submitted 2025-10-31 · 💻 cs.IT · math.IT

Dual-Scale Antenna Deployment for Pinching Antenna Systems

Xu Gan , Zhaolin Wang , Yuanwei Liu This is my paper

Pith reviewed 2026-05-21 20:17 UTC · model grok-4.3

classification 💻 cs.IT math.IT
keywords pinching antenna systemsdual-scale deploymentenergy efficiencyantenna position optimizationalternating optimizationcell-free architectureMIMO systems
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The pith

Dual-scale deployment of pinching antennas yields nearly twofold energy efficiency gains over MIMO systems.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper proposes a dual-scale deployment framework for pinching antenna systems that moves antennas coarsely along waveguides at large scales and then fine-tunes their positions with high precision in small regions. This combined optimization of antenna locations, transmit precoding, and radiation power is solved through a penalty-based alternating algorithm while keeping complexity low. The authors also build a practical power consumption model and derive closed-form energy efficiency expressions to evaluate performance. A sympathetic reader would care because better antenna positioning can reduce wasted transmit power and improve how well signals reach users without adding more hardware.

Core claim

The dual-scale deployment framework optimizes pinching antenna positions simultaneously at the coarse waveguide scale and the fine local scale, jointly with precoding and power allocation, to maximize energy efficiency; this produces theoretical expressions and simulation results showing roughly 70 percent higher efficiency than cell-free architectures and nearly twofold gains relative to MIMO systems.

What carries the argument

The dual-scale deployment (DSD) framework, which performs coarse-scale transfers of the pinching antenna over large waveguide distances together with fine-scale high-precision adjustments inside small regions.

If this is right

  • The framework delivers about 70 percent higher energy efficiency than conventional cell-free architectures.
  • It achieves nearly twofold energy efficiency improvement compared with standard MIMO systems.
  • The penalty-based alternating optimization algorithm converges while solving the joint precoding, power, and deployment problem at low complexity.
  • Theoretical energy efficiency expressions match simulated performance for the optimized dual-scale placements.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same coarse-plus-fine positioning idea could transfer to other movable or fluid antenna systems where mechanical adjustment is feasible.
  • Real deployments may need to add models for waveguide attenuation or control overhead that the current power consumption expressions omit.
  • The efficiency gains suggest fewer total antennas or lower overall network power draw could suffice to serve the same users.
  • Extending the optimization to account for user mobility or imperfect channel knowledge would test whether the reported gains remain stable.

Load-bearing premise

The practical power consumption model and the derived theoretical energy efficiency expressions accurately reflect real hardware behavior, and the penalty-based alternating optimization algorithm reliably reaches high-quality solutions for the non-convex joint problem.

What would settle it

A direct measurement of energy efficiency in a hardware prototype that implements the proposed dual-scale pinching antenna adjustments, compared against cell-free and MIMO baselines under the same user locations and power constraints.

Figures

Figures reproduced from arXiv: 2510.27185 by Xu Gan, Yuanwei Liu, Zhaolin Wang.

Figure 1
Figure 1. Figure 1: The concept of PASS signal propagation. systems; 2) the impact of DSD resolutions on energy efficiency is more pronounced in multi-PA systems; 3) the STT protocol provides over 80% improvement in energy efficiency due to the sliding-tuning gain, while the SAT protocol delivers the highest energy efficiency among the four protocols. C. Organization and Notations The remainder of this paper is structured as … view at source ↗
Figure 2
Figure 2. Figure 2: Schematic diagram of four protocols in the proposed [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Theoretical results of energy efficiency with Monte [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: Comparison with MIMO and cell-free architectures, [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 4
Figure 4. Figure 4: Convergence behavior of Algorithm 1 and 2. [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
Figure 3
Figure 3. Figure 3: This benefit arises from the carefully designed trans [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 6
Figure 6. Figure 6: Energy efficiency in Algorithm 2 under different num [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Comparison under high and low resolution for coarse [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
read the original abstract

A dual-scale deployment (DSD) framework is proposed for pinching antenna systems (PASS), under which four protocols are provided. 1) For the coarse-scale deployment, the pinching antenna (PA) is transferred over a large-scale range at the waveguide level. 2) For the fine-scale deployment, the PA is adjusted with high precision within a small-scale region. By simultaneously optimizing both scales, the proposed DSD framework can unleash the full potential of PA deployment, while maintaining low computational complexity. Based on this framework, we establish a practical power consumption model and derive theoretical energy efficiency expressions for PASS. Then, an energy-efficiency maximization problem is formulated to jointly optimize the transmit precoding, PA radiation power, and dual-scale PA deployment. To solve this non-convex, highly coupled problem, a low-complexity penalty-based alternating optimization algorithm is proposed. Simulation results validate the accuracy of theoretical results and the convergence of the proposed algorithm. It is demonstrated that the proposed DSD framework is highly effective for PASS, delivering about $70\%$ higher energy efficiency than the conventional cell-free architecture and nearly a \emph{twofold} improvement relative to MIMO systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes a dual-scale deployment (DSD) framework for pinching antenna systems (PASS) that combines coarse-scale waveguide-level PA transfer with fine-scale high-precision adjustment. It establishes a practical power consumption model, derives closed-form theoretical energy-efficiency (EE) expressions, formulates a non-convex joint optimization problem over transmit precoding, PA radiation power, and dual-scale deployment variables, and solves the problem with a penalty-based alternating optimization (AO) algorithm. Simulations are used to verify the accuracy of the theoretical EE expressions, demonstrate algorithm convergence, and report performance gains of approximately 70% higher EE relative to conventional cell-free architectures and nearly twofold improvement over MIMO systems.

Significance. If the practical power consumption model correctly captures all relevant hardware terms (including any deployment-related overhead) and the penalty-based AO algorithm reliably reaches high-quality solutions, the DSD framework would constitute a meaningful advance for energy-efficient operation of PASS. The headline quantitative claims are load-bearing for the paper’s contribution; their credibility therefore depends directly on the fidelity of the power model and the optimization procedure.

major comments (2)
  1. [Power consumption model section] The practical power consumption model (introduced prior to the EE expressions) appears to omit or under-represent terms such as waveguide propagation losses and the additional power required for mechanical coarse-scale adjustments. Because the theoretical EE expressions are derived directly from this model, any under-accounting of these costs would systematically inflate the reported gains (70% over cell-free, twofold over MIMO). A concrete sensitivity analysis or explicit inclusion of these terms is needed to support the central performance claims.
  2. [Algorithm and simulation results] The penalty-based AO algorithm is claimed to solve the non-convex joint optimization problem with low complexity and to converge reliably. However, the manuscript provides limited evidence (e.g., no comparison against global optimization benchmarks or exhaustive search on small instances) that the obtained solutions are near-optimal rather than locally good. This directly affects the validity of the simulated EE improvements.
minor comments (2)
  1. [System model] Notation for the coarse-scale and fine-scale variables should be introduced with a clear table or diagram early in the paper to avoid ambiguity when they appear in the optimization problem.
  2. [Introduction / Framework description] The abstract states that four protocols are provided under the DSD framework, yet the main text does not explicitly enumerate or compare them; a short dedicated subsection would improve readability.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive feedback on our manuscript. We address each major comment below and outline the revisions we intend to implement to strengthen the paper.

read point-by-point responses

  1. Referee: [Power consumption model section] The practical power consumption model (introduced prior to the EE expressions) appears to omit or under-represent terms such as waveguide propagation losses and the additional power required for mechanical coarse-scale adjustments. Because the theoretical EE expressions are derived directly from this model, any under-accounting of these costs would systematically inflate the reported gains (70% over cell-free, twofold over MIMO). A concrete sensitivity analysis or explicit inclusion of these terms is needed to support the central performance claims.

    Authors: We appreciate the referee pointing out potential omissions in the power consumption model. Our model was intended to capture the dominant power terms relevant to PASS, including radiation and circuit powers. However, we acknowledge that explicit modeling of waveguide propagation losses and mechanical power for coarse-scale PA adjustments was not included. In the revised manuscript, we will update the power consumption model to incorporate these terms and include a sensitivity analysis to evaluate their effect on the reported energy efficiency improvements. This will help validate the robustness of our performance claims. revision: yes

  2. Referee: [Algorithm and simulation results] The penalty-based AO algorithm is claimed to solve the non-convex joint optimization problem with low complexity and to converge reliably. However, the manuscript provides limited evidence (e.g., no comparison against global optimization benchmarks or exhaustive search on small instances) that the obtained solutions are near-optimal rather than locally good. This directly affects the validity of the simulated EE improvements.

    Authors: We agree that additional evidence for the solution quality of the penalty-based AO algorithm would enhance the paper. The algorithm employs penalty functions to manage the non-convex constraints and has demonstrated reliable convergence in our simulations. To address this concern, we will include comparisons with exhaustive search methods on small-scale problem instances in the revised version. For larger systems, we will discuss the practical limitations of global optimization approaches and why the AO method provides a good trade-off between performance and complexity. revision: partial

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper proposes a dual-scale deployment framework, establishes a practical power consumption model as an input assumption, derives energy-efficiency expressions directly from that model, formulates an optimization problem, and solves it via a penalty-based alternating optimization algorithm. Simulation results then compare performance against baselines under the same model. This constitutes standard modeling and optimization workflow rather than any reduction of predictions to fitted values or self-referential definitions by construction. No self-citations, uniqueness theorems, or ansatzes smuggled via prior work are indicated in the abstract or description. The derivation remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Based on abstract only, no explicit free parameters, axioms, or invented entities are identifiable; the power consumption model and optimization algorithm likely rest on standard domain assumptions in wireless communications.

pith-pipeline@v0.9.0 · 5730 in / 990 out tokens · 37737 ms · 2026-05-21T20:17:47.932872+00:00 · methodology

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Energy Efficiency Maximization for Discrete Activation based NOMA-assisted Pinching-Antenna Systems

    eess.SP 2026-04 unverdicted novelty 4.0

    A matching-based outer layer and closed-form inner power allocation solve the mixed-integer EE maximization problem for NOMA-assisted pinching-antenna systems, yielding gains over fixed-antenna baselines while approac...

  2. Pinching Antenna Systems (PASS): Enabling Reconfigurable and Controllable Wireless Channels -- A Comprehensive Survey

    cs.IT 2026-04 unverdicted novelty 2.0

    The paper provides a comprehensive review and categorization of pinching antenna systems (PASS) for objectives including network coverage, data rate, secure transmission, sensing, integrated sensing and communication,...

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