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Dual-Scale Antenna Deployment for Pinching Antenna Systems

Xu Gan, Zhaolin Wang, Yuanwei Liu

TL;DR

This work tackles energy-efficient PA deployment for PASS by introducing a dual-scale deployment (DSD) framework that separates coarse base sliding from fine PA tuning. It develops four deployment protocols STT, STA, SAT, and SAA and a practical power-consumption model, deriving the energy-efficiency metric $\eta_{EE} = \frac{B \sum_{k} R_k}{P_{all}}$ under the framework. A penalty-based alternating optimization algorithm is proposed to jointly optimize transmit precoding $\mathbf{W}$, PA radiation $\bm{\Xi}$, and PA positions $\mathbf{X}$, using Lagrange duality, Riemannian manifold optimization, and two-stage grid searches. Numerical results show PASS achieving about $70\%$ EE gain over conventional cell-free and nearly $2\times$ gain over MIMO, with EE highly sensitive to DSD resolution and the deployment protocol chosen. The study provides a practical roadmap for energy-efficient dual-scale PA deployment in PASS and highlights directions for protocol design and dual-scale channel estimation.

Abstract

A dual-scale deployment (DSD) framework for pinching antenna systems (PASS) is proposed. 1) In the first coarse stage, the pinching antenna (PA) is transferred over a large-scale range at the waveguide level. 2) The refinement stage performs small-scale relocation of the PA with high precision. Four PA deployment protocols are provided in the proposed DSD framework. Then, a practical power consumption model is proposed, based on which the theoretical energy efficiency formulas for PASS are derived. The transmit precoding, PA radiation power, and PA deployment are jointly optimized to maximize the energy efficiency under the provided PA deployment protocols. 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: 1) PASS delivers about 70% higher energy efficiency than the conventional cell-free architecture and nearly twofold improvement relative to MIMO systems; 2) it is essential to specify the DSD resolution and deployment protocol to achieve the maximum energy efficiency for PASS.

Dual-Scale Antenna Deployment for Pinching Antenna Systems

TL;DR

This work tackles energy-efficient PA deployment for PASS by introducing a dual-scale deployment (DSD) framework that separates coarse base sliding from fine PA tuning. It develops four deployment protocols STT, STA, SAT, and SAA and a practical power-consumption model, deriving the energy-efficiency metric under the framework. A penalty-based alternating optimization algorithm is proposed to jointly optimize transmit precoding , PA radiation , and PA positions , using Lagrange duality, Riemannian manifold optimization, and two-stage grid searches. Numerical results show PASS achieving about EE gain over conventional cell-free and nearly gain over MIMO, with EE highly sensitive to DSD resolution and the deployment protocol chosen. The study provides a practical roadmap for energy-efficient dual-scale PA deployment in PASS and highlights directions for protocol design and dual-scale channel estimation.

Abstract

A dual-scale deployment (DSD) framework for pinching antenna systems (PASS) is proposed. 1) In the first coarse stage, the pinching antenna (PA) is transferred over a large-scale range at the waveguide level. 2) The refinement stage performs small-scale relocation of the PA with high precision. Four PA deployment protocols are provided in the proposed DSD framework. Then, a practical power consumption model is proposed, based on which the theoretical energy efficiency formulas for PASS are derived. The transmit precoding, PA radiation power, and PA deployment are jointly optimized to maximize the energy efficiency under the provided PA deployment protocols. 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: 1) PASS delivers about 70% higher energy efficiency than the conventional cell-free architecture and nearly twofold improvement relative to MIMO systems; 2) it is essential to specify the DSD resolution and deployment protocol to achieve the maximum energy efficiency for PASS.

Paper Structure

This paper contains 26 sections, 1 theorem, 66 equations, 8 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Prior Works
  3. Motivations and Contributions
  4. Organization and Notations
  5. Dual-Scale Deployment Protocols for PASS
  6. Signal Model for PASS
  7. Four Implementation Protocols in the DSD Framework
  8. System Model and Problem Formulation
  9. Signal Model
  10. Energy Efficiency
  11. Problem Formulation
  12. Energy Efficiency Optimization Design
  13. Problem Reformulation
  14. Penalty-based Alternating Optimization Algorithm
  15. Subproblem w.r.t. $\mathbf{W}$
  16. ...and 11 more sections

Key Result

Lemma 1

The energy efficiency maximum problem can be transformed into where the optimization variables are Besides, the auxiliary variables $\mathbf{t}$, $\bm{\kappa}$ and $q$ are updated by $\kappa_k = \epsilon_k^{-1}$, and $q = \frac{B \cdot\sum_{k=1}^K R_k }{P_{all}}$ at every iteration.

Figures (8)

  • Figure 1: The concept of PASS signal propagation.
  • Figure 2: Schematic diagram of four protocols in the proposed DSD framework.
  • Figure 3: Theoretical results of energy efficiency with Monte Carlo results.
  • Figure 4: Convergence behavior of Algorithm 1 and 2.
  • Figure 5: Comparison with MIMO and cell-free architectures, for $\varrho=230$ and $c_{\varrho}=1/0.9$.
  • ...and 3 more figures

Theorems & Definitions (4)

  • Remark 1
  • Lemma 1
  • proof
  • Remark 2