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Environment-Aware Network-Level Design of Pinching-Antenn...
[Submitted on 19 Feb 2026 (v1), last revised 11 Sep 2026 (this v · 2026-02-19 · via cs.IT updates on arXiv.org

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Abstract:Existing studies on pinching-antenna systems have primarily focused on link-level design, where system parameters are optimized for a given user set according to user-specific communication metrics. Such designs provide an effective means of exploiting the spatial reconfigurability of pinching antennas for short-term user-centric transmission. Complementing this perspective, this two-part paper develops an environment-aware network-level design framework, where pinching-antenna configurations are optimized according to long-term spatial information and evaluated through network-level performance metrics. 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 by explicitly modeling line-of-sight blocking and optimizing region-wide robustness objectives. 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 low-complexity 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 descent framework where each coordinate update reduces to a one-dimensional subproblem via an epigraph reformulation and bisection. Simulations show that the proposed design outperm.

Submission history

From: Yanqing Xu [view email]
[v1] Thu, 19 Feb 2026 02:38:46 UTC (648 KB)
[v2] Fri, 11 Sep 2026 00:24:52 UTC (533 KB)