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REVIEW 3 major objections 6 minor 1 cited by

Beam Training for Pinching-Antenna Systems (PASS)

T0 review · 3 major / 6 minor · reviewed 2026-08-08 · deepseek-v4-flash

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Pith's one-line read For pinching-antenna wireless systems, this paper proposes a three-stage codebook-based beam training scheme that cuts training overhead to 48 slots versus $2^{20}$ for exhaustive search, while keeping rates close to the phase-aligned…

desk verdict A legitimate first paper on beam training for pinching antennas: the codebook-as-antenna-locations idea is new, the overhead reduction is real, and the main weakness is the untested ideal-hardware assumption rather than a flawed core. read the letter →

arxiv 2502.05921 v1 pith:A32HQTBD submitted 2025-02-09 eess.SP

Suyu Lv , Yuanwei Liu , Zhiguo Ding This is my paper · ORCID
classification eess.SP
keywords beamtrainingpinching-antennasystemscodebookdesignnear-fieldcommunicationsNOMAhybridbeamforminghierarchicaloverhead
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper tries to establish that pinching-antenna systems can align beams to users without full channel estimation, by treating the physical locations of activated antennas as the beamforming design. It proposes a scalable codebook of antenna-location patterns and a three-stage beam training scheme that first localizes the user coarsely along one axis, then refines it with more antennas, then finishes with a small exhaustive search. The claimed payoff is a dramatic cut in training overhead, from $2^{20}$ slots for a two-dimensional exhaustive search to 48 slots in the simulated single-user setup, while the achievable rate approaches the phase-aligned upper bound at 28 GHz. The same codebook idea is extended to multiple users on one waveguide using NOMA and to multiple waveguides with hybrid beamforming, where choosing which waveguide serves which user adds another degree of freedom. A sympathetic reader would take the paper as showing that dynamic pinching antennas turn beam training into a location-estimation problem that can be solved cheaply and scalably.

What carries the argument

The central object is the scalable codebook, where each codeword is not a complex beamforming weight vector but a list of physical locations for the $N$ activated pinching antennas along the waveguide. For a given sampling point $\psi_f$, steps S1-S5 generate these locations by solving the modulo phase-alignment condition that combines free-space propagation phase and in-waveguide phase $\theta_n$, while maintaining a guard distance $\tilde{\Delta}$. The three-stage beam training scheme, 3SBT, then exploits this codebook: stage one activates a single antenna to estimate the user's x-coordinate from received signal strength, stage two increases the antenna count to refine the y-coordinate, and stage three runs an exhaustive search over a small remaining region. Because the codebook is scalable, new sampling points and additional antennas can be added without regenerating existing codewords, which is what makes the low-overhead hierarchy possible and lets the same design extend to multi-user and multi-waveguide cases.

What would settle it

Build or simulate a pinching-antenna setup where activation positions are quantized to a grid of spacing $\delta$ (for example $\lambda/10$) and the waveguide propagation constant has a few percent uncertainty; run the proposed 3SBT at 28 GHz and compare the final rate to the phase-aligned bound. If the gap does not shrink to near zero as training layers increase while the ideal-continuous codebook does, the perfect-placement assumption is the load-bearing part of the claim.

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Extended reading notes

Core claim

The paper's central claim is that beam training in a pinching-antenna system can be reduced to locating the user and placing antennas at the positions that make all signal phases align at the user. For a sampled user point $\psi_f$, the scalable codebook places each activated antenna at the first position along the waveguide, alternating outward from the point closest to the user, that satisfies the phase condition $\mathrm{mod}\{\frac{2\pi}{\lambda}|\psi_f-\tilde{\psi}^{\mathrm{pin}}_n|+\theta_n,2\pi\}=0$, with a guard distance $\tilde{\Delta}$ between antennas to avoid coupling. The three-stage scheme uses one antenna for a coarse x-coordinate estimate, an increasing number of antennas for y-direction phase matching, and a final partial exhaustive search over the surviving rectangle. In the simulated SWSU setup this takes $K(L_1+L_2)+K_1K_2=48$ training slots instead of $K^{L_1+L_2}K_1K_2=2^{20}$ for a 2D exhaustive search, and the rate gap to the phase-aligned bound shrinks to nearly zero at 28 GHz as training layers increase. The same codebook structure is adapted to SWMU scenarios with NOMA and to MWMU scenarios with partially-connected hybrid beamforming, with simulations showing dynamic pinching antennas outperforming fixed-location pinching antennas and conventional arrays.

Load-bearing premise

The paper assumes a pinching antenna can be activated perfectly at any exact point along the waveguide and that the waveguide phase delay at that point is known precisely, so the codeword positions computed from the modulo phase condition are physically realizable.

Editorial extensions

If this is right

  • Pinching-antenna systems can be trained with tens of slots instead of roughly a million, removing a major barrier to using them without explicit channel estimation.
  • The same scalable codebook supports multi-user NOMA training, with per-user antenna clusters and a joint exhaustive stage, so the multi-user overhead grows from one user's cost to a sum over users plus a product of small refinement subranges.
  • Multi-waveguide PASS adds a new degree of freedom, waveguide selection, and the paper's Lemma 1 states that each user gets the largest received signal strength when all its antennas sit on the closest waveguide clustered around the point nearest the user.
  • Dynamic pinching antennas outperform fixed-location pinching antennas and conventional uniform linear arrays at equal power in the simulations, with the gain growing as the number of activated antennas increases.
  • Phase-alignment performance is better at higher carrier frequencies, because the shorter wavelength makes the codebook's discretization errors smaller relative to the user distance.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If continuous antenna placement is relaxed to a discrete grid, the codebook generation steps could be rounded to the nearest feasible positions; the hierarchical training would still work, but the achievable-rate gap would then depend on the grid spacing, which is a testable extension the paper does not run.
  • The scheme's coarse first stage relies on received signal strength scaling with distance, which is most reliable in line-of-sight near-field settings; in rich multipath or heavily blocked environments the one-antenna localization step could point to the wrong x-region and the later stages would inherit that error.
  • The multi-user and multi-waveguide results use equal power splitting and no digital precoding optimization, so jointly optimizing power allocation and precoding with the codebook-based training is a natural next step that could push sum rates above the reported equal-power curves.
  • The overhead comparison assumes the codebook, once generated, can be reused; in a mobile setting the hierarchical first stage could be run periodically to track the user, with the later stages reusing the stored codewords, but tracking behavior is not studied in the paper.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper proposes beam-training designs for pinching-antenna systems (PASS) in three scenarios: single-waveguide-single-user (SWSU), single-waveguide-multi-user (SWMU), and multi-waveguide-multi-user (MWMU). For each scenario it introduces a scalable codebook generated by solving phase-alignment conditions (S1-S5), and a three-stage hierarchical beam training (3SBT) scheme that first estimates the user's x-coordinate with a single antenna, then refines the y-coordinate with an increasing number of antennas, and finally performs a partial exhaustive search. The paper claims that this reduces training overhead from 2^20 slots to 48 slots in the SWSU setup of Table I while maintaining reasonable rate performance, and that dynamic pinching antennas outperform fixed-location pinching antennas and conventional arrays. Numerical results for a single fixed geometry are presented at 28 GHz and 5 GHz.

Significance. If the claims hold, the paper makes a useful contribution: it gives a systematic, scalable codebook construction and a hierarchical training protocol for a new antenna architecture, with a correct and easily verified overhead count in Table I (48 vs. 2^20 slots for the SWSU case). The extension to NOMA-based SWMU and to partially-connected hybrid beamforming in MWMU broadens the applicability. However, the validation is currently much narrower than the claims: all simulations are deterministic and use a single user geometry per scenario, and the underlying model assumes ideal continuous placement and perfect knowledge of waveguide phase. The central overhead reduction is a counting argument and is sound; the rate-performance claim is plausible but is not yet supported by sensitivity analysis or statistical results.

major comments (3)
  1. [Section II-A, Eq. (1), and S1-S5] The codebook construction S1-S5 requires exact antenna positions satisfying mod{2π/λ |ψ_f - ψpin_n| + θ_n, 2π}=0, which presupposes continuous placement resolution and perfect knowledge of the waveguide phase θ_n. This ideal assumption, stated in Section II-A, is not stress-tested anywhere in Section V: all figures are generated under the same model, and no sweep over placement granularity or phase error is reported. Since a placement or phase error changes the received power of every codeword and can mislead the hierarchical decisions in Algorithm 2, the central claim that 3SBT achieves reasonable rate with low overhead is currently only established for an idealized, perfectly calibrated hardware model. The authors should add a robustness study or explicitly reframe the claims as ideal-theoretic.
  2. [Section V-A, Figs. 7-8 and Table I] The rate-performance claim is supported by a single deterministic user location, ψU=(5,4,0), with fixed L1, L2, K, and dES settings. There is no averaging over user positions or channel realizations, and the paper does not plot the rate achieved by the 2D exhaustive-search baseline of Table I; Fig. 8 compares against the phase-aligned upper bound, which is a different reference. To make the comparison complete, please include an exhaustive-search rate curve and report statistics (mean/percentiles) over multiple user geometries, and state whether the 48-slot overhead always identifies the same codeword as the exhaustive search.
  3. [Section III-B1, Stage 1 of Algorithm 3] In the separated user training stage, the received signal at Um contains contributions from all antenna clusters because the same waveguide carries the superimposed NOMA signal, but the paper assumes that large-scale fading makes the desired cluster's signal dominate. This assumption is stated without a quantitative condition or numerical validation. If the clusters are not sufficiently separated, the measured |r_m| used for hierarchy decisions is corrupted by inter-cluster interference, and Stage 1 can select a wrong sub-range. Please provide a quantitative condition (e.g., minimum inter-user distance or power ratio) under which the assumption holds, and show the sensitivity of Stage-1 accuracy to this parameter.
minor comments (6)
  1. [Section I, final paragraph] The sentence "Sections II, III and IV focus on SWSU-PASS, SWSU-PASS and SWSU-PASS respectively" should read SWSU, SWMU, and MWMU.
  2. [Algorithm 2, Stage 2] In the formula N' = min{2^{l+1-L1}, N}, clarify that l continues from L1+1 when the second while loop begins; otherwise the exponent is undefined at the start of the stage.
  3. [Eq. (20) and Section V-C] The waveguide phase term uses a single feed point ψpin_0, but in Section V-C each waveguide has a different feed point; please define ψpin_0,q for each waveguide or state that a common reference is used.
  4. [References [8] and [9]] "Preprint" is misspelled as "Prepint" in both references.
  5. [Fig. 8] The 5 GHz curve does not converge, and the text attributes this to larger guard distances and discretization errors; a sentence explaining the connection between wavelength, guard distance (Δ=λ/2), and phase error would aid the reader.
  6. [Table I] For SWMU with M=3, the proposed overhead is 4192 slots, which is much larger than the M=2 value; the paper should note that Stage 3 grows as the product of per-user candidate counts and discuss complexity for larger M.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: 3SBT is a genuine codebook search; codebook construction and evaluation share the same stated channel model, and the overhead reduction follows from algorithmic counting rather than from any fitted or self-cited result.

full rationale

The paper's central claim is that a three-stage hierarchical beam-training scheme reduces training overhead versus 2D exhaustive search while keeping rate performance reasonable. I traced the derivation chain from the system model (Eq. (1)) through codebook construction (S1–S5), the 3SBT algorithm (Algorithm 2), and the overhead expressions in Table I. No step reduces to its own inputs by construction. The codebook codewords are defined as pinching-antenna locations satisfying a modulo phase-alignment condition for a given sampling point; beam training then selects among these codewords using the received signal strength computed from the same spherical-wave channel model. This is a standard model-based codebook search, not a fitted input renamed as a prediction: there are no parameters fitted to a subset of data and then used to 'predict' the same data, and no benchmark result is obtained by definitional identity. The convergence of the simulated rate toward the phase-aligned upper bound in Fig. 8 is an expected property of an algorithm whose codewords are phase-aligning by design, not a circular validation. The overhead numbers in Table I follow directly from the stated layer counts and exhaustive-search sub-range divisions. Self-citations [8] and [9] supply the pinching-antenna architecture and channel model used as assumptions; these are parameter-free modeling premises that do not themselves assert the paper's beam-training overhead or rate results, so they do not constitute load-bearing circularity. The paper's 'ideal scenario' of perfectly controllable continuous antenna placement is a genuine hardware-idealization limitation, but it is an assumption about realizability, not a circularity in the derivation.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The central training scheme does not fit any free parameter to data; the codebook is a deterministic mapping. However, it leans on several idealizations: continuous antenna placement, exact waveguide phase, and a LoS-only channel. The multi-user extension adds an unoptimized reclustering threshold. These are domain assumptions rather than hidden fitted constants.

free parameters (2)
  • reclustering distance threshold \tilde{d}
    Introduced in Section III-B2 (Algorithm 3) to decide when to merge antenna clusters for nearby users; no value is specified or optimized in the paper.
  • guard distance \tilde{\Delta} = lambda/2 (simulation)
    Set to half wavelength in simulation (Section V) to avoid antenna coupling; physically motivated but chosen by hand and affects codeword geometry.
assumptions (5)
  • domain assumption LoS-only spherical wave channel model with no multipath or shadowing (Eq. (1))
    The entire codebook design and training metric assume free-space pathloss and phase only; real indoor/outdoor channels would include reflections.
  • ad hoc to paper Ideal continuous activation of pinching antennas at any location on the waveguide (Section II-A)
    The codebook codewords are exact antenna locations that solve a phase equation; if activation is discrete or imprecise, the codewords are not realizable.
  • domain assumption Known waveguide phase theta_n = 2*pi/lambda_g * |psi_pin0 - psi_pin_n| with fixed effective index neff (Eq. (1))
    The phase-matching equations S1-S5 rely on exact knowledge of propagation phase along the waveguide; dispersion or manufacturing variation would break them.
  • ad hoc to paper Existence of a solution to the modulo phase condition on the designated waveguide segment (S1-S5)
    The codebook algorithm searches for the first location satisfying mod{...}=0 but no existence or uniqueness proof is given; the waveguide must be long enough.
  • ad hoc to paper In SWMU stage 1, interference from other user clusters is negligible because large-scale fading dominates (Section III-B1)
    The simultaneous multi-cluster training treats each user's signal as dominated by its own cluster; this is asserted, not derived.

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Cite this review

Pith. "Pith review of Beam Training for Pinching-Antenna Systems (PASS)." pith.science (2026). https://pith.science/paper/A32HQTBD

@misc{pith2026250205921,
  author       = {Pith},
  title        = {Pith review of: Beam Training for Pinching-Antenna Systems (PASS)},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/A32HQTBD}},
  note         = {Machine review of arXiv:2502.05921}
}
read the original abstract

This article investigates the beam training design problems for pinching-antenna systems (PASS), where single-waveguide-single-user (SWSU), single-waveguide-multi-user (SWMU) and multi-waveguide-multi-user (MWMU) scenarios are considered. For SWSU-PASS, we design a scalable codebook, based on which we propose a three-stage beam training (3SBT) scheme. Specifically, 1) firstly, the 3SBT scheme utilizes one activated pinching antenna to obtain a coarse one-dimensional location at the first stage; 2) secondly, it achieves further phase matching with an increased number of activated antennas at the second stage; 3) finally, it realizes precise beam alignment through an exhaustive search at the third stage. For SWMU-PASS, based on the scalable codebook design, we propose an improved 3SBT scheme to support non-orthogonal multiple access (NOMA) transmission. For MWMU-PASS, we first present a generalized expression of the received signal based on the partially-connected hybrid beamforming structure. Furthermore, we introduce an increased-dimensional scalable codebook design, based on which an increased-dimensional 3SBT scheme is proposed. Numerical results reveal that: i) the proposed beam training scheme can significantly reduce the training overhead compared to the two-dimensional exhaustive search, while maintaining reasonable rate performance; ii) compared to fixed-location pinching antennas and conventional array antennas, the proposed dynamic pinching antennas yield better flexibility and improved performance.

Figures

Figures reproduced from arXiv: 2502.05921 by the authors.

Figure 1
Figure 1. Illustration of PASS. wave model is more appropriate to be used in PASS. Recall that with the spherical wave model, the CSI contains both angular and distance domains [12], resulting in a significant overhead for near-field beam training, especially in large￾scale MIMO systems. To achieve a balance between training performance and training overhead, [13] and [14] proposed hierarchical training schemes. Specifically,… view at source ↗
Figure 2
Figure 2. Illustration for the three-stage beam training scheme. [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Illustration of SWMU-PASS. SWSU-PASS is summarized in Algorithm 2. III. SINGLE-WAVEGUIDE PASS SERVING MULTIPLE USERS In this section, we focus on the scenario of SWMU￾PASS. Firstly, we introduce the system model of NOMA-based SWMU-PASS. Subsequently, based on the scalable codebook generation design, we propose an improved 3SBT scheme. The details are presented in the following subsections, respectively. A. System Mo… view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Illustration of MWMU-PASS. height of d, where the y-coordinate of the q-th waveguide is y wg q . Denote the n-th pinching antenna on the q-th waveguide by ⟨q, n⟩-th antenna, with its location denoted by ψ˜pin q,n, where q = 1, · · · , Q and n = 1, · · · , N. The number…
Figure 5
Figure 5. Figure 5: Illustration of partially-connected hybrid beamforming structure. [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Achievable rate versus phase upon reaching the user, i.e., mod n 2π λ [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 9
Figure 9. Figure 9: Achievable rate versus number of antennas. [PITH_FULL_IMAGE:figures/full_fig_p011_9.png]
Figure 12
Figure 12. Figure 12: Achievable sum rate versus transmission power. 6 12 18 24 30 36 Number of activated antennas on each waveguide 15 20 25 30 35 Achievable sum rate (bits/s/Hz) Dynamic Pinc., NOMA Dynamic Pinc., TDMA Fixed Pinc., NOMA Fixed Pinc., TDMA Conv., NOMA Conv., TDMA 6 12 18 24…

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Forward citations

Cited by 1 Pith paper

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

  1. Beamforming Design for Pinching Antenna Systems with Multiple Receive Antennas

    eess.SP 2025-09 conditional novelty 6.0 of 10

    A two-layer placement algorithm for pinching antennas that aligns signals across multiple receive antennas improves rate over single-antenna-oriented schemes, especially at close range.

Reference graph

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