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arxiv: 2601.06430 · v3 · pith:JSPNVLDMnew · submitted 2026-01-10 · 💻 cs.IT · eess.SP· math.IT

Robust and Secure Blockage-Aware Pinching Antenna-assisted Wireless Communication

Pith reviewed 2026-05-22 12:09 UTC · model grok-4.3

classification 💻 cs.IT eess.SPmath.IT
keywords pinching antennarobust optimizationsecure communicationblockage awarenessartificial noiseimperfect CSIsum rate maximizationgeometry-aware uncertainty
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The pith

A pinching-antenna system with adaptive positioning and geometry-aware uncertainty sets maximizes secure sum rates under blockages and imperfect CSI.

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

The paper establishes that repositioning pinching antennas along waveguides, combined with new uncertainty sets for eavesdropper location and orientation errors, enables robust secure communication that outperforms fixed-antenna designs. A sympathetic reader would care because real environments contain obstacles that block signals and adversaries whose channels are only partially known. The approach injects artificial noise to degrade eavesdroppers while jointly optimizing beamforming, power splits, and antenna locations to serve legitimate users. This yields higher overall rates and stronger secrecy guarantees by preserving clear paths to intended receivers and exploiting geometry to weaken unwanted links.

Core claim

The authors develop geometry-aware uncertainty sets that jointly characterize eavesdropper position and array-orientation errors for spatially distributed pinching-antenna architectures. They formulate a robust optimization problem that jointly designs per-waveguide beamforming and artificial-noise covariance, individual antenna power ratios, and antenna positions to maximize the system sum rate subject to secrecy constraints under blockage effects and imperfect CSI. The nonconvex problem is solved by an iterative algorithm based on block coordinate descent, penalty methods, majorization minimization, the S-procedure, and Lipschitz-based surrogate functions. Simulations show the resulting 4.

What carries the argument

geometry-aware uncertainty sets that jointly characterize eavesdropper position and array-orientation errors

If this is right

  • Adaptive pinching-antenna positioning preserves line-of-sight paths to legitimate users while using waveguide geometry to disrupt eavesdropper channels.
  • Neglecting blockage effects in the pinching-antenna design causes measurable rate loss and insufficient secrecy protection.
  • The iterative algorithm converges to a high-performance solution by alternating between beamforming, noise covariance, power allocation, and position updates.
  • The resulting system delivers substantially higher sum rates and secrecy performance than conventional fixed-antenna baselines.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same positioning freedom could be used to track slowly moving users and maintain secrecy as blockages change over time.
  • Extending the uncertainty sets to include hardware imperfections in the waveguides themselves would make the robustness claims more complete.
  • Testing the design on measured outdoor or indoor channel data with actual obstacles would reveal how much of the reported gain survives real propagation.

Load-bearing premise

The geometry-aware uncertainty sets accurately and non-conservatively model the joint eavesdropper position and array-orientation errors for spatially distributed pinching antenna architectures under blockage effects.

What would settle it

Compare the secrecy rates obtained from the optimized pinching-antenna design against measured rates when real eavesdropper positions and array orientations deviate from the modeled uncertainty sets by known amounts.

Figures

Figures reproduced from arXiv: 2601.06430 by Deepak Mishra, Derrick Wing Kwan Ng, Ruotong Zhao, Shaokang Hu.

Figure 1
Figure 1. Figure 1: A downlink PAs-assisted communication system. [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Illustration of the ULA of EA g, depicting the antenna indexing, blockage regions, and the orientation angle θg, with respect to the position x-axis. Furthermore, there are G non-cooperative potential EAs, in￾dexed by the set G ≜ {1, . . . , G}. In practice, each EA is equipped with a uniform linear array (ULA) comprising T > 1 antenna elements, enhancing their capability to intercept the confidential tran… view at source ↗
Figure 4
Figure 4. Figure 4: Illustration of the available power allocation among PAs along the [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Proposed channel error bound when N = 5, M = 2, and T = 2. from the maximum curvature [47]. Accordingly, the (i3 + 1)- th iteration of the penalty-based MM method for stage 2 of the PA positioning problem can be expressed as: maximize x Pin n , Ak, ι, δ, A E g , θˆi,k, θˆE ¯i,g, θl(n,m),k, θE l(n,m,t),g X k∈K log2 (ι N k +ι D k +σ 2 k )+R¯(ι D(i3) k ) − ρ1 X K k=1 MN X i=2 Γˆ (i3) i,k − ρ2 X G g=1 MNT X ¯i… view at source ↗
Figure 1
Figure 1. Figure 1: We set the smoothing parameter, number of blockages, [PITH_FULL_IMAGE:figures/full_fig_p014_1.png] view at source ↗
Figure 6
Figure 6. Figure 6: Convergence of the proposed algorithm against multiple benchmarks [PITH_FULL_IMAGE:figures/full_fig_p015_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Average achievable sum rate versus the total transmit power budget [PITH_FULL_IMAGE:figures/full_fig_p015_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Average sum rate versus the maximum normalized channel estimation [PITH_FULL_IMAGE:figures/full_fig_p016_8.png] view at source ↗
read the original abstract

In this work, we investigate a blockage-aware pinching antenna (PA) system designed for secure and robust wireless communication. The considered system comprises a base station equipped with multiple waveguides, each hosting multiple PAs, and serves multiple single-antenna legitimate users in the presence of multi-antenna eavesdroppers under imperfect channel state information (CSI). To safeguard confidential transmissions, artificial noise (AN) is deliberately injected to degrade the eavesdropping channels. Recognizing that conventional linear CSI error bounds become overly conservative for spatially distributed PA architectures, we develop new geometry aware uncertainty sets that jointly characterize eavesdropper position and array-orientation errors. Building upon these sets, we formulate a robust joint optimization problem that determines per waveguide beamforming and AN covariance, individual PA power ratio allocation, and PA positions to maximize the system sum rate subject to secrecy constraints. The highly nonconvex design problem is efficiently addressed via a low computational complexity iterative algorithm that capitalizes on block coordinate descent, penalty based methods, majorization minimization, the S procedure, and Lipschitz based surrogate functions. Simulation results demonstrate that the sum rate achieved by the proposed algorithm outperforms conventional fixed-antenna systems by 4.7 dB, offering substantially improved rate and secrecy performance. In particular, (i) adaptive PA positioning preserves LoS to legitimate users while effectively exploiting waveguide geometry to disrupt eavesdropper channels, and (ii) neglecting blockage effects in the PA system significantly impacts the system design, leading to performance degradation and inadequate secrecy guarantees.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes a blockage-aware pinching antenna (PA) system for secure wireless communication serving multiple users in the presence of multi-antenna eavesdroppers under imperfect CSI. It develops new geometry-aware uncertainty sets that jointly model eavesdropper position and array-orientation errors while accounting for blockage effects, then formulates a robust sum-rate maximization problem incorporating artificial noise, per-waveguide beamforming, power allocation, and PA positioning. The non-convex problem is solved via an iterative algorithm using block coordinate descent, majorization minimization, penalty methods, the S-procedure, and Lipschitz surrogates. Simulations report a 4.7 dB sum-rate gain over fixed-antenna baselines with improved secrecy performance.

Significance. If the geometry-aware uncertainty sets are shown to be tight and non-conservative, the work could meaningfully advance robust secure designs for distributed PA architectures in blockage-prone settings by exploiting adaptive positioning to maintain LoS for legitimate users while disrupting eavesdroppers. The explicit treatment of blockage-induced LoS/NLoS transitions and the low-complexity iterative solver are practical strengths. The reported performance gains, however, rest on the validity of these sets; without supporting validation the significance remains conditional.

major comments (2)
  1. [Uncertainty set construction and robust formulation] The geometry-aware uncertainty sets (introduced to replace conventional linear CSI error bounds) are load-bearing for the robust formulation and the 4.7 dB gain claim. The manuscript provides no Monte-Carlo validation comparing the worst-case secrecy rate predicted by these sets against the true worst-case rate obtained from explicit random realizations of joint position/orientation perturbations drawn from the same physical blockage model. This leaves open whether the sets are overly conservative (artificially lowering achievable rate) or insufficiently tight (under-protecting secrecy).
  2. [Simulation results] Simulation results section: the headline 4.7 dB sum-rate improvement is obtained by solving the robust problem with the proposed sets. The paper should report whether the sets were validated for tightness on the same channel realizations used for benchmarking, and whether any post-hoc parameter tuning was performed; absent this, the gain relative to the fixed-antenna baseline cannot be fully attributed to the new modeling approach.
minor comments (2)
  1. [Algorithm development] Clarify the convergence criterion and typical number of iterations for the BCD/MM/penalty loop in the algorithm description to support the low-complexity claim.
  2. [System model] Ensure all symbols for PA positions, waveguide geometry, and blockage probabilities are defined consistently before first use.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive feedback on our manuscript. We address the major comments point by point below, and we will incorporate revisions to enhance the clarity and validation of our proposed uncertainty sets.

read point-by-point responses
  1. Referee: [Uncertainty set construction and robust formulation] The geometry-aware uncertainty sets (introduced to replace conventional linear CSI error bounds) are load-bearing for the robust formulation and the 4.7 dB gain claim. The manuscript provides no Monte-Carlo validation comparing the worst-case secrecy rate predicted by these sets against the true worst-case rate obtained from explicit random realizations of joint position/orientation perturbations drawn from the same physical blockage model. This leaves open whether the sets are overly conservative (artificially lowering achievable rate) or insufficiently tight (under-protecting secrecy).

    Authors: We appreciate the referee's emphasis on validating the tightness of the geometry-aware uncertainty sets. These sets are constructed directly from the physical model of eavesdropper position and array-orientation errors under blockage effects, using the S-procedure and Lipschitz surrogates to ensure robustness. However, we acknowledge that the manuscript does not include explicit Monte-Carlo simulations to compare the worst-case rates from the sets against sampled realizations. To address this, we will add a new subsection in the revised manuscript presenting Monte-Carlo validation results on the same channel realizations used for the performance benchmarks. This will demonstrate that the sets provide a tight bound without excessive conservatism. revision: yes

  2. Referee: [Simulation results] Simulation results section: the headline 4.7 dB sum-rate improvement is obtained by solving the robust problem with the proposed sets. The paper should report whether the sets were validated for tightness on the same channel realizations used for benchmarking, and whether any post-hoc parameter tuning was performed; absent this, the gain relative to the fixed-antenna baseline cannot be fully attributed to the new modeling approach.

    Authors: We agree that additional clarification is warranted in the simulation results section. The parameters for the uncertainty sets are derived analytically from the geometry and blockage model without any post-hoc tuning to achieve the reported gains. The 4.7 dB improvement stems from the adaptive PA positioning and joint optimization enabled by these sets. In the revision, we will explicitly report that no post-hoc tuning was performed and include the Monte-Carlo validation on the benchmarking realizations to confirm the attribution of the performance gains to the proposed modeling. revision: yes

Circularity Check

0 steps flagged

No circularity: new uncertainty sets and simulation gains are independent of fitted outputs

full rationale

The paper introduces geometry-aware uncertainty sets as a modeling contribution to handle joint position and orientation errors under blockage, then applies standard robust optimization tools (S-procedure, BCD, MM, penalty methods) to maximize sum rate subject to secrecy constraints. The 4.7 dB gain is obtained from Monte-Carlo simulations against fixed-antenna baselines and does not reduce to any quantity defined by the optimization variables or by self-citation of prior results from the same authors. No step equates a claimed performance metric to a fitted parameter or renames an input as a prediction; the derivation remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 1 invented entities

The paper adds a new modeling construct (geometry-aware sets) and an optimization framework. No large set of fitted constants or invented physical entities; the uncertainty sets are the primary modeling addition.

axioms (1)
  • domain assumption Imperfect CSI characterized by position and orientation errors for multi-antenna eavesdroppers in the presence of blockages.
    Invoked to motivate and construct the geometry-aware uncertainty sets for the robust formulation.
invented entities (1)
  • Geometry-aware uncertainty sets no independent evidence
    purpose: To jointly model eavesdropper position and array-orientation errors in a manner suitable for spatially distributed pinching antennas.
    New modeling construct introduced to avoid overly conservative linear bounds.

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Reference graph

Works this paper leans on

47 extracted references · 47 canonical work pages

  1. [1]

    Resource allocation for multi-waveguide pinching antenna-assisted broadcast networks,

    R. Zhao, S. Hu, D. Mishra, and D. W. K. Ng, “Resource allocation for multi-waveguide pinching antenna-assisted broadcast networks,”arXiv preprint arXiv:2507.03915, 2025

  2. [2]

    Movable antenna-enhanced multiuser communication: Jointly optimal discrete an- tenna positioning and beamforming,

    Y . Wu, D. Xu, D. W. K. Ng, W. Gerstacker, and R. Schober, “Movable antenna-enhanced multiuser communication: Jointly optimal discrete an- tenna positioning and beamforming,” inProc. IEEE Global Telecommun. Conf, Dec. 2023, pp. 7508–7513

  3. [3]

    Fluid antenna systems,

    K.-K. Wong, A. Shojaeifard, K.-F. Tong, and Y . Zhang, “Fluid antenna systems,”IEEE Trans. Wirelss Commun., vol. 20, no. 3, pp. 1950–1962, Mar. 2021

  4. [4]

    Flexible-antenna systems: A pinching-antenna perspective,

    Z. Ding, R. Schober, and H. V . Poor, “Flexible-antenna systems: A pinching-antenna perspective,”IEEE Trans. Commun., vol. 73, no. 10, pp. 9236–9253, Oct. 2025

  5. [5]

    Pinching-antenna systems (PASS): Power radiation model and optimal beamforming design,

    X. Xu, X. Mu, Z. Wang, Y . Liu, and A. Nallanathan, “Pinching-antenna systems (PASS): Power radiation model and optimal beamforming design,”arXiv preprint arXiv:2505.00218, 2025

  6. [6]

    Modeling and beam- forming optimization for pinching-antenna systems,

    Z. Wang, C. Ouyang, X. Mu, Y . Liu, and Z. Ding, “Modeling and beam- forming optimization for pinching-antenna systems,”IEEE Trans. Com- mun., early access, Oct. 13, 2025, doi: 10.1109/TCOMM.2025.3621049

  7. [7]

    MIMO pinching- antenna-aided SWIPT,

    H. Li, Z. Lyu, Y . Gao, M. Xiao, and H. V . Poor, “MIMO pinching- antenna-aided SWIPT,”IEEE Wireless Commun. Lett., early access, Oct. 08, 2025, doi: 10.1109/LWC.2025.3618988

  8. [8]

    Minimum data rate maximization for uplink pinching-antenna systems,

    S. A. Tegos, P. D. Diamantoulakis, Z. Ding, and G. K. Karagiannidis, “Minimum data rate maximization for uplink pinching-antenna systems,” IEEE Wireless Commun. Lett., vol. 14, no. 5, pp. 1516–1520, May 2025

  9. [9]

    Joint radiation power, antenna position, and beamforming optimization for pinching- antenna systems with motion power consumption,

    Y . Xu, D. Xu, X. Yu, S. Song, Z. Ding, and R. Schober, “Joint radiation power, antenna position, and beamforming optimization for pinching- antenna systems with motion power consumption,”arXiv preprint arXiv:2507.02348, 2025

  10. [10]

    Multiple UA V-borne IRS-aided millimeter wave multicast communications: A joint optimization framework,

    K. Guo, C. Wang, Z. Li, D. W. K. Ng, and K.-K. Wong, “Multiple UA V-borne IRS-aided millimeter wave multicast communications: A joint optimization framework,”IEEE Commun. Lett, vol. 25, no. 11, pp. 3674–3678, Nov. 2021

  11. [11]

    Trajectory design and resource allocation for multi-UA V communications under blockage-aware channel model,

    P. Yi, L. Zhu, Z. Xiao, R. Zhang, Z. Han, and X.-G. Xia, “Trajectory design and resource allocation for multi-UA V communications under blockage-aware channel model,”IEEE Trans. Commun., vol. 72, no. 4, pp. 2324–2338, Apr. 2024

  12. [12]

    LoS blockage in pinching-antenna systems: Curse or blessing?

    Z. Ding and H. V . Poor, “LoS blockage in pinching-antenna systems: Curse or blessing?”IEEE Wireless Commun. Lett., vol. 14, no. 9, pp. 2798–2802, Sep. 2025

  13. [13]

    Pinching-antenna systems with LoS blockages,

    K. Wang, C. Ouyang, Y . Liu, and Z. Ding, “Pinching-antenna systems with LoS blockages,”IEEE Wireless Commun. Lett., early access, Sep. 24, 2025, doi: 10.1109/LWC.2025.3614451

  14. [14]

    Joint 3D positioning and power allocation for UA V relay aided by geographic information,

    P. Yi, L. Zhu, L. Zhu, Z. Xiao, Z. Han, and X.-G. Xia, “Joint 3D positioning and power allocation for UA V relay aided by geographic information,”IEEE Trans. Wireless Commun., vol. 21, no. 10, pp. 8148– 8162, Oct. 2022

  15. [15]

    Robust and secure wireless communications via intelligent reflecting surfaces,

    X. Yu, D. Xu, Y . Sun, D. W. K. Ng, and R. Schober, “Robust and secure wireless communications via intelligent reflecting surfaces,”IEEE J. Sel. Areas Commun., vol. 38, no. 11, pp. 2637–2652, Nov. 2020

  16. [16]

    Robust secure communications in near-field ISCAP systems with extremely large-scale antenna array,

    Z. Ren, S. Zhang, L. Qiu, D. W. K. Ng, and J. Xu, “Robust secure communications in near-field ISCAP systems with extremely large-scale antenna array,”arXiv preprint arXiv:2505.15279, 2025

  17. [17]

    Pinching-antenna systems for physical layer security,

    K. Wang, Y . Liu, and Z. Ding, “Pinching-antenna systems for physical layer security,”IEEE Wireless Commun. Lett., early access, Oct. 23, 2025, doi: 10.1109/LWC.2025.3624885

  18. [18]

    Physical layer security for pinching-antenna systems (PASS),

    M. Sun, C. Ouyang, S. Wu, and Y . Liu, “Physical layer security for pinching-antenna systems (PASS),”arXiv preprint arXiv:2503.09075, 2025

  19. [19]

    Physical-layer security of pinching-antenna systems,

    O. S. Badarneh, H. S. Silva, and Y . H. A. Badarneh, “Physical-layer security of pinching-antenna systems,”arXiv preprint arXiv:2503.18322, 2025

  20. [20]

    Sensing-assisted eavesdropper esti- mation: An ISAC breakthrough in physical layer security,

    N. Su, F. Liu, and C. Masouros, “Sensing-assisted eavesdropper esti- mation: An ISAC breakthrough in physical layer security,”IEEE Trans. Wireless Commun., vol. 23, no. 4, pp. 3162–3174, Apr. 2024

  21. [21]

    Channel estima- tion for mmWave pinching-antenna systems,

    G. Zhou, V . Papanikolaou, Z. Ding, and R. Schober, “Channel estima- tion for mmWave pinching-antenna systems,” inProc. IEEE 26th Int. Workshop Signal Process. Adv. Wireless Commun. (SPAWC), Jul. 2025, pp. 1–5

  22. [22]

    Robust beam- forming design for RIS-aided cell-free systems with CSI uncertainties and capacity-limited backhaul,

    J. Yao, J. Xu, W. Xu, D. W. K. Ng, C. Yuen, and X. You, “Robust beam- forming design for RIS-aided cell-free systems with CSI uncertainties and capacity-limited backhaul,”IEEE Trans. Wireless Commun., vol. 71, no. 8, pp. 4636–4649, Aug. 2023

  23. [23]

    Robust beamforming design for near-field DMA-NOMA mmwave communications with imperfect position information,

    Y . Xiu, Y . Zhao, S. Yang, Y . Zhang, D. Niyato, H. Du, and N. Wei, “Robust beamforming design for near-field DMA-NOMA mmwave communications with imperfect position information,”IEEE Trans. Wireless Commun., vol. 24, no. 2, pp. 1678–1692, Feb. 2025

  24. [24]

    Robust and secure sum-rate maximization for multiuser MISO downlink systems with self-sustainable IRS,

    S. Hu, Z. Wei, Y . Cai, C. Liu, D. W. K. Ng, and J. Yuan, “Robust and secure sum-rate maximization for multiuser MISO downlink systems with self-sustainable IRS,”IEEE Trans. Commun., vol. 69, no. 10, pp. 7032–7049, Oct. 2021

  25. [25]

    Robust resource allocation for pinching-antenna systems under imperfect CSI,

    M. Zeng, X. Wang, Y . Liu, Z. Ding, G. K. Karagiannidis, and H. V . Poor, “Robust resource allocation for pinching-antenna systems under imperfect CSI,”arXiv preprint arXiv:2507.12582, 2025

  26. [26]

    Sum-rate max- imization for pinching antenna-assisted NOMA systems with multiple dielectric waveguides,

    S. Hu, R. Zhao, Y . Liao, D. W. K. Ng, and J. Yuan, “Sum-rate max- imization for pinching antenna-assisted NOMA systems with multiple dielectric waveguides,”arXiv preprint arXiv:2503.10060, 2025

  27. [27]

    C. A. Balanis,Balanis’ Advanced Engineering Electromagnetics. John Wiley & Sons, 2024

  28. [28]

    R. J. Mailloux,Phased array antenna handbook. Artech house, 2017

  29. [29]

    Channel estimation for extremely large-scale MIMO: Far-field or near-field?

    M. Cui and L. Dai, “Channel estimation for extremely large-scale MIMO: Far-field or near-field?”IEEE Trans. Commun., vol. 70, no. 4, pp. 2663–2677, Apr. 2022

  30. [30]

    Pinching-antenna systems: Architecture designs, opportunities, and outlook,

    Y . Liu, Z. Wang, X. Mu, C. Ouyang, X. Xu, and Z. Ding, “Pinching-antenna systems: Architecture designs, opportunities, and outlook,”IEEE Commun. Mag., early access, Sep. 17, 2025, doi: 10.1109/MCOM.001.2500037

  31. [31]

    MIMO- PASS: Uplink and downlink transmission via MIMO pinching-antenna systems,

    A. Bereyhi, C. Ouyang, S. Asaad, Z. Ding, and H. V . Poor, “MIMO- PASS: Uplink and downlink transmission via MIMO pinching-antenna systems,”arXiv preprint arXiv:2503.03117, 2025

  32. [32]

    Investigation of prediction accuracy, sensitivity, and parameter stability of large-scale propagation path loss models for 5G wireless communications,

    S. Sun, T. S. Rappaport, T. A. Thomas, A. Ghosh, H. C. Nguyen, I. Z. Kovacs, I. Rodriguez, O. Koymen, and A. Partyka, “Investigation of prediction accuracy, sensitivity, and parameter stability of large-scale propagation path loss models for 5G wireless communications,”IEEE Trans. Veh. Technol., vol. 65, no. 5, pp. 2843–2860, May 2016

  33. [33]

    Robust beamform- ing design for secure near-field ISAC systems,

    Z. Chen, F. Wang, G. Han, X. Wang, and V . K. Lau, “Robust beamform- ing design for secure near-field ISAC systems,”IEEE Wireless Commun. Lett., vol. 14, no. 10, pp. 3089–3093, Oct. 2025

  34. [34]

    Location information assisted beamforming design for reconfigurable intelligent surface aided com- munication systems,

    Z. Xing, R. Wang, X. Yuan, and J. Wu, “Location information assisted beamforming design for reconfigurable intelligent surface aided com- munication systems,”IEEE Trans. Wireless Commun., vol. 22, no. 11, pp. 7676–7695, Nov. 2023

  35. [35]

    Rate maximization for downlink pinching-antenna systems,

    Y . Xu, Z. Ding, and G. K. Karagiannidis, “Rate maximization for downlink pinching-antenna systems,”IEEE Wireless Commun. Lett., vol. 14, no. 5, pp. 1431–1435, May 2025

  36. [36]

    Pinching antenna: Using a dielectric waveguide as an antenna,

    H. O. Y . Suzuki and K. Kawai, “Pinching antenna: Using a dielectric waveguide as an antenna,”NTT DOCOMO Technical J, 2022

  37. [37]

    Localization in massive MIMO networks: From Far-Field to Near-Field,

    P. Ramezani, ¨O. Tu˘gfe Demir, and E. Bj¨ornson, “Localization in massive MIMO networks: From Far-Field to Near-Field,”Massive MIMO for Future Wireless Communication Systems: Technology and Applications, pp. 123–150, 2025

  38. [38]

    Array partitioning based near-field attitude and location estimation,

    M. Zhang, X. Yuan, B. Teng, and L. Wang, “Array partitioning based near-field attitude and location estimation,” inProc. 16th Int. Conf. Wireless Commun. Signal Process. (WCSP), Oct. 2024, pp. 813–818

  39. [39]

    Direction-of-arrival estimation with virtual antenna array: Observability analysis, local oscillator frequency offset compensation, and experimental results,

    J. Cheng, K. Guan, and F. Quitin, “Direction-of-arrival estimation with virtual antenna array: Observability analysis, local oscillator frequency offset compensation, and experimental results,”IEEE Trans. Instrum. Meas., vol. 70, pp. 1–13, Jun. 2021

  40. [40]

    Multiple emitter location and signal parameter estimation,

    R. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Trans. Antennas Propag., vol. 34, no. 3, pp. 276–280, Mar. 1986

  41. [41]

    Okamoto,Fundamentals of optical waveguides

    K. Okamoto,Fundamentals of optical waveguides. Elsevier, 2021

  42. [42]

    Multiple antennas and beamforming for SWIPT systems

    D. W. K. Ng, S. Leng, and R. Schober, “Multiple antennas and beamforming for SWIPT systems.” 2016

  43. [43]

    Pinching- antenna systems (PASS)-enabled secure wireless communications,

    G. Zhu, X. Mu, L. Guo, S. Xu, Y . Liu, and N. Al-Dhahir, “Pinching- antenna systems (PASS)-enabled secure wireless communications,” arXiv preprint arXiv:2504.13670, 2025

  44. [44]

    Globally optimal movable antenna-enabled multiuser communication: Discrete antenna positioning, power consumption, and imperfect CSI,

    Y . Wu, D. Xu, D. W. K. Ng, W. Gerstacker, and R. Schober, “Globally optimal movable antenna-enabled multiuser communication: Discrete antenna positioning, power consumption, and imperfect CSI,”IEEE Trans. Commun., vol. 73, no. 10, pp. 9903–9923, Oct. 2025

  45. [45]

    Amplitude- dependent phase-gradient directional beamforming for IRS: A scalable optimization framework,

    Z. Mao, W. Wang, Q. Xia, C. Huang, X. Pan, and Z. Ye, “Amplitude- dependent phase-gradient directional beamforming for IRS: A scalable optimization framework,”IEEE Trans. wirelss Commun., vol. 72, no. 4, pp. 2354–2369, Apr. 2024

  46. [46]

    IRS-assisted green communication systems: Provable convergence and robust optimization,

    X. Yu, D. Xu, D. W. K. Ng, and R. Schober, “IRS-assisted green communication systems: Provable convergence and robust optimization,” IEEE Trans. Commun., vol. 69, no. 9, pp. 6313–6329, Sep. 2021

  47. [47]

    Incremental majorization-minimization optimization with application to large-scale machine learning,

    J. Mairal, “Incremental majorization-minimization optimization with application to large-scale machine learning,”SIAM J. Optim., vol. 25, no. 2, pp. 829–855, 2015