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Environment-Aware Network-Level Design of Generalized Pinching-Antenna Systems--Part I: Traffic-Aware Case

Yanqing Xu, Zhiguo Ding, Xiu Yin Zhang, Trung Q. Duong, Tsung-Hui Chang

TL;DR

The paper addresses network-level design for generalized pinching-antenna systems in traffic-dominated environments, identifying the gap that link-level optimization cannot fill. It introduces a traffic-aware framework with a grid-based approximation and a traffic-weighted network average-SNR metric, and formulates two deployment problems: maximizing the traffic-weighted network average SNR and maximizing the minimum average SNR over active grids. The first problem is solved via a candidate-based global maximization exploiting the unimodal, hotspot-induced components, while the second uses a BCD framework with an epigraph reformulation and inner bisection to obtain globally optimal 1D subproblem solutions. Numerical results show that traffic-aware placement significantly outperforms fixed and heuristic deployments, with robust performance across region size, hotspot configurations, and network settings, highlighting the practical value for region-wide service quality and fairness. These results lay the groundwork for Part II, which will tackle geometry-aware design in obstacle-rich environments.

Abstract

Existing studies on generalized pinching-antenna systems are predominantly link-level, which optimize system parameters for a given user set with objectives defined by per-user performance metrics. Such designs do not capture network-level requirements, e.g., region-wide coverage and location fairness, and may require frequent re-optimization as users move or enter/leave, incurring control overhead and sensitivity to localization errors. Motivated by this gap, this two-part paper aims to develop an environment-aware network-level design framework for generalized pinching-antenna systems. Part I focuses on the traffic-aware case, where user presence is modeled statistically by a spatial traffic map and performance is optimized and evaluated in a traffic-aware sense; Part II addresses the geometry-aware case in obstacle-rich environments. In Part~I, we introduce traffic-weighted average SNR metrics and formulate two traffic-aware deployment problems: (i) maximizing the traffic-weighted network average SNR, and (ii) a fairness-oriented traffic-restricted max--min average-SNR design over traffic-dominant grids. To solve these nonconvex problems with low complexity, we reveal and exploit their separable structures. For the network-average objective, we establish unimodality properties of the hotspot-induced components and develop a candidate-based global maximization method that only needs to evaluate the objective at a small set of candidate antenna positions. For the traffic-restricted max--min objective, we develop a block coordinate decent framework where each coordinate update reduces to a globally solvable one-dimensional subproblem via an epigraph reformulation and bisection. Simulations show that traffic-aware pinching-antenna positioning consistently outperforms representative fixed and heuristic traffic-aware deployments in the considered setups.

Environment-Aware Network-Level Design of Generalized Pinching-Antenna Systems--Part I: Traffic-Aware Case

TL;DR

The paper addresses network-level design for generalized pinching-antenna systems in traffic-dominated environments, identifying the gap that link-level optimization cannot fill. It introduces a traffic-aware framework with a grid-based approximation and a traffic-weighted network average-SNR metric, and formulates two deployment problems: maximizing the traffic-weighted network average SNR and maximizing the minimum average SNR over active grids. The first problem is solved via a candidate-based global maximization exploiting the unimodal, hotspot-induced components, while the second uses a BCD framework with an epigraph reformulation and inner bisection to obtain globally optimal 1D subproblem solutions. Numerical results show that traffic-aware placement significantly outperforms fixed and heuristic deployments, with robust performance across region size, hotspot configurations, and network settings, highlighting the practical value for region-wide service quality and fairness. These results lay the groundwork for Part II, which will tackle geometry-aware design in obstacle-rich environments.

Abstract

Existing studies on generalized pinching-antenna systems are predominantly link-level, which optimize system parameters for a given user set with objectives defined by per-user performance metrics. Such designs do not capture network-level requirements, e.g., region-wide coverage and location fairness, and may require frequent re-optimization as users move or enter/leave, incurring control overhead and sensitivity to localization errors. Motivated by this gap, this two-part paper aims to develop an environment-aware network-level design framework for generalized pinching-antenna systems. Part I focuses on the traffic-aware case, where user presence is modeled statistically by a spatial traffic map and performance is optimized and evaluated in a traffic-aware sense; Part II addresses the geometry-aware case in obstacle-rich environments. In Part~I, we introduce traffic-weighted average SNR metrics and formulate two traffic-aware deployment problems: (i) maximizing the traffic-weighted network average SNR, and (ii) a fairness-oriented traffic-restricted max--min average-SNR design over traffic-dominant grids. To solve these nonconvex problems with low complexity, we reveal and exploit their separable structures. For the network-average objective, we establish unimodality properties of the hotspot-induced components and develop a candidate-based global maximization method that only needs to evaluate the objective at a small set of candidate antenna positions. For the traffic-restricted max--min objective, we develop a block coordinate decent framework where each coordinate update reduces to a globally solvable one-dimensional subproblem via an epigraph reformulation and bisection. Simulations show that traffic-aware pinching-antenna positioning consistently outperforms representative fixed and heuristic traffic-aware deployments in the considered setups.
Paper Structure (25 sections, 5 theorems, 58 equations, 8 figures, 2 tables)

This paper contains 25 sections, 5 theorems, 58 equations, 8 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Models and Performance Metrics
  3. System Model
  4. Channel Model with Random LoS and NLoS Components
  5. Traffic Model
  6. Traffic-Aware Network Performance Metric
  7. Grid-Based Approximation
  8. Traffic-Weighted Average-SNR Optimization
  9. Per-Grid and Network Average SNR Derivations
  10. Problem Formulation
  11. Problem Structure Analysis and Low-Complexity Algorithm Design
  12. Shape of Each Hotspot-Induced Component $F_{n,\ell}(\widetilde{x}_n)$
  13. Two-Hotspot Case: Merge--Split Behavior
  14. Extension to the Multi-Hotspot Case
  15. Traffic-Restricted Max--Min Average-SNR Optimization
  16. ...and 10 more sections

Key Result

Lemma 1

For a given pinching-antenna deployment $\widetilde{\boldsymbol{x}}$, the local average SNR in grid $(u,v)$ admits the closed-form expression where $r_{n,u,v}(\widetilde{\boldsymbol{x}}) = \sqrt{(x_u - \widetilde{x}_n)^2 + C_n}$ denotes the distance between pinching antenna $n$ and grid $(u,v)$. With the traffic weights $\{p_{u,v}\}$, the corresponding traffic-aware network average SNR is given b

Figures (8)

  • Figure 1: Traffic-aware pinching-antenna systems.
  • Figure 2: Traffic-weighted network average-SNR performance comparison among the proposed algorithm with two baselines.
  • Figure 3: Traffic-aware network average SNR comparisons between different schemes versus the number of antennas $N$.
  • Figure 4: Traffic-aware network average-SNR comparisons between different schemes versus the communication-region length $D_x$.
  • Figure 5: Worst active-grid average SNR comparisons with baselines versus the number of antennas $N$ for the traffic-restricted max-min design.
  • ...and 3 more figures

Theorems & Definitions (6)

  • Lemma 1
  • Lemma 2
  • Lemma 3
  • Proposition 1
  • Remark 1
  • Proposition 2