On the Maintainability of Pinching-Antenna Systems: A Failure-Repair Perspective

The pinching-antenna system (PASS) enables wireless channel reconfiguration through optimized placement of pinching antennas along dielectric waveguides. In this article, a unified analytical framework is proposed to characterize the maintainability of PASS. Within this framework, random waveguide failures and repairs are modeled by treating the waveguide lifetime and repair time as exponentially distributed random variables, which are characterized by the failure rate and the repair rate, respectively. The operational state of the waveguide is described by a two-state continuous-time Markov chain, for which the transition probabilities and steady-state probabilities of the waveguide being working or failed are analyzed. By incorporating the randomness of the waveguide operational state into the transmission rate, system maintainability is characterized using the probability of non-zero rate (PNR) and outage probability (OP). The proposed framework is applied to both a conventional PASS employing a single long waveguide and a segmented waveguide-enabled pinching-antenna system (SWAN) composed of multiple short waveguide segments under two operational protocols: segment switching (SS) and segment aggregation (SA). Closed-form expressions for the PNR and OP are derived for both architectures, and the corresponding scaling laws are analyzed with respect to the service-region size and the number of segments. It is proven that both SS-based and SA-based SWAN achieve higher PNR and lower OP than conventional PASS, which confirms the maintainability advantage of segmentation. Numerical results demonstrate that: i) the maintainability gain of SWAN over conventional PASS increases with the number of segments, and ii) SA provides stronger maintainability than SS.

💡 Research Summary

This paper presents a rigorous analytical framework for evaluating the maintainability of Pinching‑Antenna Systems (PASS) and introduces a segmented‑waveguide architecture, termed SWAN, that substantially improves reliability and service continuity. The authors begin by modeling the lifetime and repair time of a dielectric waveguide as exponential random variables characterized by a failure rate λ (per unit length) and a repair rate μ. Under this assumption the operational state of each waveguide is described by a two‑state continuous‑time Markov chain (CTMC) with “working” and “failed” states. Closed‑form expressions for the time‑dependent transition probabilities and the steady‑state probabilities π_W (working) and π_F (failed) are derived, capturing the stochastic nature of waveguide availability.

To connect availability with communication performance, the authors embed the CTMC state into the received signal‑to‑noise ratio (SNR). When the waveguide is operational, the SNR follows the conventional PASS model; when it is failed, the transmission rate collapses to zero. This binary rate model leads to two key performance metrics: the Probability of Non‑Zero Rate (PNR) = π_W·Pr{γ > γ_th} and the Outage Probability (OP) = π_F + π_W·Pr{γ ≤ γ_th}, where γ_th is a target SNR threshold. These metrics provide a direct, probabilistic measure of maintainability and reliability.

For a conventional PASS that uses a single, long waveguide of length L, the authors show that PNR decays quadratically with L (PNR ∝ L⁻²). This scaling law reveals a fundamental limitation: as the service region expands, the likelihood of a failure somewhere along the waveguide grows, dramatically reducing the chance of successful transmission.

To overcome this limitation, the paper proposes the Segmented‑Waveguide‑Enabled Pinching‑Antenna System (SWAN). SWAN replaces the monolithic guide with M short segments, each of length L/M, each equipped with its own feed point and at most one active pinching antenna (PA). The segments are electrically independent; their outputs are conveyed to the base station via low‑loss wired links (optical fiber or coaxial cable). Because each segment can be repaired independently, the overall working probability becomes π_W^SWAN = 1 – (λ/(λ+μ))^M, which increases rapidly with the number of segments.

Two operational protocols are examined:

1. Segment Switching (SS) – When a segment fails, the system simply switches to another working segment, using only one PA at a time. The authors derive closed‑form expressions for PNR_SS and OP_SS, showing that both improve monotonically with M and always outperform the monolithic PASS.

2. Segment Aggregation (SA) – All working segments transmit simultaneously, and their SNRs are coherently combined at the receiver. A closed‑form expression for PNR_SA is obtained, and an analytically tractable upper bound for OP_SA is derived. The scaling analysis demonstrates that PNR_SA grows faster with M than PNR_SS, and OP_SA converges to its lower limit more quickly, establishing SA as the superior protocol in terms of maintainability.

The theoretical results are validated by extensive Monte‑Carlo simulations. Using realistic failure (λ = 10⁻⁴ s⁻¹) and repair (μ = 10⁻³ s⁻¹) rates, the simulations confirm that: (i) both SS‑based and SA‑based SWAN achieve significantly higher PNR and lower OP than conventional PASS; (ii) the performance gap widens as the service region (i.e., total waveguide length) increases; (iii) SA consistently outperforms SS in both metrics; and (iv) increasing the number of segments yields diminishing outage probabilities and near‑deterministic non‑zero rates.

In conclusion, the paper provides the first quantitative, closed‑form treatment of PASS maintainability, demonstrates the inherent scalability problem of monolithic waveguides, and proves that segmenting the waveguide—especially with the aggregation protocol—offers a practical pathway to highly reliable, low‑maintenance reconfigurable antenna systems for future 6G and beyond networks. The work opens several avenues for future research, including non‑exponential failure models, multi‑user resource allocation in SWAN, and experimental validation with real dielectric waveguide hardware.