pith. sign in

arxiv: 2605.23851 · v1 · pith:SDRYU4CLnew · submitted 2026-05-22 · 📡 eess.SP

A Manifold-Based Framework for Coupling-Aware Surrogate Optimization of Antenna Arrays Using Characteristic Modes

Pith reviewed 2026-05-25 03:00 UTC · model grok-4.3

classification 📡 eess.SP
keywords antenna array synthesismutual couplingcharacteristic modessurrogate optimizationmanifold optimizationgeneralized scattering matrixphased arrayleft-handed circular polarization
0
0 comments X

The pith

A manifold-based surrogate using characteristic modes and global coupling models enables fast optimization of antenna arrays that accounts for mutual coupling.

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

The paper develops a surrogate optimization method for antenna arrays that includes the effects of mutual coupling between elements while remaining computationally light. It formulates the design using a shared characteristic mode basis across the array, models coupling globally, and constrains each element's generalized scattering matrix to lie on the manifold of unitary symmetric matrices to enforce reciprocity and losslessness. A staged penalty approach handles pattern constraints during optimization of multi-beam arrays. This matters because it lets designers explore non-uniform element configurations that better meet requirements than uniform ones, with the process completing in seconds and verified by full-wave simulations.

Core claim

The framework combines a common characteristic-mode basis, a global modal coupling model, and element-wise generalized scattering matrices (GSMs) whose design variables are optimized on the manifold of unitary symmetric matrices. For an 8x8 left-handed circularly polarized patch array, different degree-of-freedom strategies show that non-identical element classes can meet strict sidelobe and cross-polarization requirements where identical elements cannot. The optimization runs in seconds, and full-wave checks confirm the predicted sidelobe levels with good accuracy and cross-polarization with useful accuracy.

What carries the argument

Optimization of element generalized scattering matrices on the manifold of unitary symmetric matrices, combined with a global modal coupling model based on a common characteristic-mode basis.

If this is right

  • Optimization of an 8x8 array converges in seconds on one CPU core.
  • Non-identical element classes satisfy pattern constraints that equal-element designs cannot.
  • Full-wave verification matches the surrogate for sidelobe level and provides useful accuracy for cross-polarization ratio.
  • The approach scales to practical array synthesis while incorporating coupling.

Where Pith is reading between the lines

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

  • The method may allow rapid redesign for varying scan angles or frequencies by reusing the modal basis.
  • Extending the manifold to include loss could broaden applicability to real antennas with dissipation.
  • Application to arrays with irregular layouts might test the generality of the global coupling model.
  • Comparison with gradient-based or evolutionary surrogates could show whether the manifold constraint reduces the evaluations needed for convergence.

Load-bearing premise

The characteristic-mode basis and modal coupling model are assumed to represent mutual coupling effects accurately enough that the surrogate optimization yields arrays whose full-wave performance matches the predictions, based on demonstration with a single array.

What would settle it

Demonstrating a second array where the surrogate-optimized design shows substantially worse sidelobe levels or cross-polarization in full-wave simulation than predicted would indicate the coupling model is insufficient.

Figures

Figures reproduced from arXiv: 2605.23851 by Dirk Manteuffel, Leonardo M\"orlein.

Figure 1
Figure 1. Figure 1: Schematic overview of the proposed approach. [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 3
Figure 3. Figure 3: Signal flow representation of the k-th antenna element with original (left) and phase-shifted reference plane (right). The identical incident (a (k) ) and radiated (f (k) ) mode coefficients are shared between both configurations. the eigenvalues λe(k) n in the diagonal of Se(k) 0,eig = diag 1 − jλe(k) n 1 + jλe(k) n (41) and the quasi-orthogonal modal transformation matrix Qe (k) , which maps coefficients… view at source ↗
Figure 2
Figure 2. Figure 2: Schematic overview of the proposed approach with repeated opti [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 5
Figure 5. Figure 5: Initial element. The element has been tuned to achieve LHCP in the [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Array pattern of the initial array constructed using a pattern [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Different strategies for the assignment of the degrees of freedom [PITH_FULL_IMAGE:figures/full_fig_p008_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Penalty αl , optimization cost φ and total optimization time vs. iteration. The vertical dashed lines denote the iteration indices where the penalty term was increased αl → αl+1. elements; and Alternating assigns one degree of freedom to each of two alternating element groups. Next, the manifold of the excitations is defined. Because the feeding network in [PITH_FULL_IMAGE:figures/full_fig_p009_8.png] view at source ↗
Figure 11
Figure 11. Figure 11: Analysis of the first terminated antenna element for different values ()() [PITH_FULL_IMAGE:figures/full_fig_p010_11.png] view at source ↗
Figure 10
Figure 10. Figure 10: Comparison of the achieved high level parameters (a) directivity of [PITH_FULL_IMAGE:figures/full_fig_p010_10.png] view at source ↗
Figure 12
Figure 12. Figure 12: Geometric realization (a) of the k-th antenna element shown together with the dependence of the eigenvalue (b) λ (k) 1 on the electrical length of the resonant edge for this mode l (k) 1 /λ0. The dependence of the eigenvalue λ (k) 2 on the edge length l (k) 2 /λ0 is similar and is therefore not shown. The rotation angle ϕ (k) does not influence the eigenvalues. The edge length l1 of the patch antenna is t… view at source ↗
Figure 14
Figure 14. Figure 14: Comparison of (a) the desired GSM Ψ′(1) and (b) the realized GSM Ψˆ (1) of first element of the EdgeCornerInternal array. The colormap that encodes the magnitude and phase is the same for both matrices and is shown in (c). 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 1 2 63 64 x/Dx y/Dy [PITH_FULL_IMAGE:figures/full_fig_p011_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: Final array geometry for the PointSymmetry array, which consists [PITH_FULL_IMAGE:figures/full_fig_p011_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: Comparison of the achieved far-field between the far-field predicted [PITH_FULL_IMAGE:figures/full_fig_p012_16.png] view at source ↗
read the original abstract

A surrogate-based synthesis framework for antenna arrays is presented that incorporates mutual coupling while keeping optimization computationally efficient. The method combines a common characteristic-mode basis, a global modal coupling model, and element-wise generalized scattering matrices (GSMs). Array design variables are formulated and optimized on physically meaningful manifolds, in particular the manifold of unitary symmetric matrices for reciprocal and lossless element GSMs. A staged penalty strategy is used to progressively enforce sidelobe and cross-polarization constraints during multi-beam optimization. The framework is demonstrated for an 8x8 left-handed circularly polarized patch phased array with scan behavior in one principal plane. Different degree-of-freedom assignment strategies are compared, showing that constrained non-identical element classes can satisfy stringent pattern requirements where equal-element designs fail. For the demonstrated case, the optimization converges within seconds on a single CPU core, and full-wave verification of the realized arrays confirms the predicted trends, with good agreement for the SLL and useful accuracy for the XPR. The results indicate that the proposed formulation is a practical and scalable route for coupling-aware array synthesis and realization.

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

1 major / 1 minor

Summary. The paper presents a surrogate-based synthesis framework for antenna arrays incorporating mutual coupling via a common characteristic-mode basis, global modal coupling model, and element-wise generalized scattering matrices (GSMs). Array variables are optimized on manifolds (e.g., unitary symmetric matrices for reciprocal lossless GSMs) using a staged penalty strategy for sidelobe and cross-polarization constraints. The method is demonstrated on an 8x8 left-handed circularly polarized patch phased array with one-plane scan, where optimization is fast and full-wave verification shows good SLL agreement and useful XPR accuracy; different DOF assignment strategies are compared, with constrained non-identical elements succeeding where equal-element designs fail. The results suggest the approach is a practical route for coupling-aware array synthesis.

Significance. If the reduced-order model proves accurate beyond the demonstrated case, the framework would provide an efficient, manifold-constrained alternative to full-wave array optimization, enabling designs with non-identical elements under coupling effects. The combination of established CM and GSM concepts with manifold optimization is a coherent extension, though the single-configuration verification limits the strength of the scalability claim.

major comments (1)
  1. [Demonstration section (abstract and results)] Demonstration section (abstract and results): Full-wave verification is reported only for the single 8x8 LHCP patch array with scan in one principal plane, showing 'good agreement' for SLL and 'useful accuracy' for XPR. This narrow regime is load-bearing for the central claim that the CM-basis + global modal coupling + element-wise GSM surrogate produces realizable arrays matching full-wave behavior; without additional geometries, frequencies, or scan ranges, it remains unclear whether model discrepancies grow outside this case or whether the optimization exploits inaccuracies.
minor comments (1)
  1. [Abstract] The abstract states that 'different degree-of-freedom assignment strategies are compared' but provides no explicit enumeration or definition of the strategies (e.g., identical vs. non-identical element classes) before the results are summarized.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the constructive feedback on the demonstration and verification aspects of the manuscript. We address the major comment below.

read point-by-point responses
  1. Referee: Demonstration section (abstract and results): Full-wave verification is reported only for the single 8x8 LHCP patch array with scan in one principal plane, showing 'good agreement' for SLL and 'useful accuracy' for XPR. This narrow regime is load-bearing for the central claim that the CM-basis + global modal coupling + element-wise GSM surrogate produces realizable arrays matching full-wave behavior; without additional geometries, frequencies, or scan ranges, it remains unclear whether model discrepancies grow outside this case or whether the optimization exploits inaccuracies.

    Authors: We acknowledge that the full-wave verification is confined to a single 8x8 LHCP patch array with one-plane scanning, which limits the strength of broader claims about scalability and robustness across regimes. This configuration was chosen to enable detailed comparison of DOF assignment strategies under realistic coupling, with the surrogate derived from general CM and GSM principles. We will revise the manuscript to explicitly state the verification scope, discuss potential model discrepancies outside this case, and qualify the scalability claim accordingly. No additional full-wave cases will be added at this stage, as the current results already demonstrate the framework's practical utility for the reported setting. revision: yes

Circularity Check

0 steps flagged

No significant circularity; framework builds on independent CM/GSM models with external full-wave verification

full rationale

The manuscript derives its surrogate model from standard characteristic-mode theory and generalized scattering matrices, then performs manifold-constrained optimization and reports independent full-wave validation on the realized 8x8 array. No step reduces a claimed prediction to a quantity defined by the same fitted parameters or to a self-citation whose content is unverified. The central result (realizable arrays matching full-wave trends) rests on the physical modeling assumptions rather than tautological re-use of its own outputs.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Based on abstract only; no explicit free parameters, invented entities, or ad-hoc axioms are identifiable beyond standard domain assumptions in antenna theory.

axioms (2)
  • domain assumption Characteristic modes form a suitable common basis for modeling array elements and their mutual coupling.
    Invoked as the foundation of the surrogate model in the abstract.
  • domain assumption Optimization on the manifold of unitary symmetric matrices preserves physical properties of reciprocal lossless GSMs.
    Used to formulate design variables.

pith-pipeline@v0.9.0 · 5723 in / 1312 out tokens · 32101 ms · 2026-05-25T03:00:06.511848+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

38 extracted references · 38 canonical work pages

  1. [1]

    T. S. Bird,Mutual Coupling Between Antennas. Wiley, 2021

  2. [2]

    A Multi-Level Optimization Method Using PSO for the Optimal Design of an L-Shaped Folded Monopole Antenna Array,

    T. H. Nguyen, H. Morishita, Y . Koyanagi, K. Izui, and S. Nishiwaki, “A Multi-Level Optimization Method Using PSO for the Optimal Design of an L-Shaped Folded Monopole Antenna Array,”IEEE Transactions on Antennas and Propagation, vol. 62, no. 1, pp. 206–215, Jan. 2014. [Online]. Available: https://ieeexplore.ieee.org/document/6655892

  3. [3]

    Performance-Based Nested Surrogate Modeling of Antenna Input Characteristics,

    S. Koziel and A. Pietrenko-Dabrowska, “Performance-Based Nested Surrogate Modeling of Antenna Input Characteristics,” IEEE Transactions on Antennas and Propagation, vol. 67, no. 5, pp. 2904–2912, May 2019. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/8631127

  4. [4]

    Multi-Objective Design of Antennas Using Variable-Fidelity Simulations and Surrogate Models,

    S. Koziel and S. Ogurtsov, “Multi-Objective Design of Antennas Using Variable-Fidelity Simulations and Surrogate Models,”IEEE Transactions on Antennas and Propagation, vol. 61, no. 12, pp. 5931–5939, Dec

  5. [5]

    Available: https://ieeexplore.ieee.org/document/6612670

    [Online]. Available: https://ieeexplore.ieee.org/document/6612670

  6. [6]

    Evolutionary Programming in Electromagnetic Optimization: A Review,

    A. Hoorfar, “Evolutionary Programming in Electromagnetic Optimization: A Review,”IEEE Transactions on Antennas and Propagation, vol. 55, no. 3, pp. 523–537, Mar. 2007. [Online]. Available: https://ieeexplore.ieee.org/document/4120264

  7. [7]

    Solving Some Array Synthesis Problems by Means of an Effective Hybrid Approach,

    M. D’Urso and T. Isernia, “Solving Some Array Synthesis Problems by Means of an Effective Hybrid Approach,”IEEE Transactions on Antennas and Propagation, vol. 55, no. 3, pp. 750–759, Mar. 2007. [Online]. Available: https://ieeexplore.ieee.org/document/4120250/

  8. [8]

    Koziel and S

    S. Koziel and S. Ogurtsov,Antenna Design by Simulation- Driven Optimization, ser. SpringerBriefs in Optimization. Cham: Springer International Publishing, 2014. [Online]. Available: https://link.springer.com/10.1007/978-3-319-04367-8

  9. [9]

    Grating-Lobe Mitigation Using Parasitic Scatterers and Principal Com- ponent Analysis,

    A. Salmi, J. Bergman, A. Lehtovuori, J. Ala-Laurinaho, and V . Viikari, “Grating-Lobe Mitigation Using Parasitic Scatterers and Principal Com- ponent Analysis,”IEEE Trans. Antennas Propag., vol. 72, no. 2, pp. 1995–2000, Feb. 2024

  10. [10]

    Synthesis of Reactively Loaded Sparse Antenna Arrays Using Optimization on Riemannian Manifold,

    A. Salmi, A. Lehtovuori, and V . Viikari, “Synthesis of Reactively Loaded Sparse Antenna Arrays Using Optimization on Riemannian Manifold,” IEEE Open J. Antennas Propag., pp. 1–1, 2024

  11. [11]

    Design of microstrip antenna subarrays: A simulation-driven surrogate-based approach,

    A. Bekasiewicz, W. Zieniutycz, S. Koziel, and S. Ogurtsov, “Design of microstrip antenna subarrays: A simulation-driven surrogate-based approach,” in2014 20th International Conference on Microwaves, Radar and Wireless Communications (MIKON), Jun. 2014, pp. 1–4. [Online]. Available: https://ieeexplore.ieee.org/document/6899849

  12. [12]

    Microstrip antenna subarray design through simulation-driven surrogate optimization,

    S. Koziel, S. Ogurtsov, and W. Zieniutycz, “Microstrip antenna subarray design through simulation-driven surrogate optimization,” in2014 IEEE Antennas and Propagation Society International Symposium (APSURSI), Jul. 2014, pp. 1724–1725. [Online]. Available: https://ieeexplore.ieee.org/document/6905188

  13. [13]

    Surrogate-Assisted Defected Ground Structure Design for Reducing Mutual Coupling in 2 × 2 Microstrip Antenna Array,

    B. Qian, X. Huang, X. Chen, M. Abdullah, L. Zhao, and A. A. Kishk, “Surrogate-Assisted Defected Ground Structure Design for Reducing Mutual Coupling in 2 × 2 Microstrip Antenna Array,”IEEE Antennas and Wireless Propagation Letters, vol. 21, no. 2, pp. 351–355, Feb

  14. [14]

    Available: https://ieeexplore.ieee.org/document/9629326

    [Online]. Available: https://ieeexplore.ieee.org/document/9629326

  15. [15]

    Simulation driven design of a microstrip antenna array by means of surrogate-based optimization,

    S. Koziel and S. Ogurtsov, “Simulation driven design of a microstrip antenna array by means of surrogate-based optimization,” in2013 7th European Conference on Antennas and Propagation (EuCAP), Apr. 2013, pp. 2182–2185. [Online]. Available: https://ieeexplore.ieee.org/document/6546679

  16. [16]

    Expedited microstrip linear antenna array design using radiation response surrogates,

    ——, “Expedited microstrip linear antenna array design using radiation response surrogates,” in2015 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, Jul. 2015, pp. 2457–2458. [Online]. Available: https://ieeexplore.ieee.org/document/7305617

  17. [17]

    Rapid simulation-based design of covered planar microstrip patch antenna arrays by means of radiation response surrogates,

    S. Koziel, S. Ogurtsov, and J. P. Jacobs, “Rapid simulation-based design of covered planar microstrip patch antenna arrays by means of radiation response surrogates,” in2015 Loughborough Antennas & Propagation Conference (LAPC), Nov. 2015, pp. 1–4. [Online]. Available: https://ieeexplore.ieee.org/document/7366081

  18. [18]

    Rapid Design Closure of Linear Microstrip Antenna Array Apertures Using Response Features,

    S. Koziel and S. Ogurtsov, “Rapid Design Closure of Linear Microstrip Antenna Array Apertures Using Response Features,”IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 4, pp. 645–648, Apr

  19. [19]

    Available: https://ieeexplore.ieee.org/document/8301557

    [Online]. Available: https://ieeexplore.ieee.org/document/8301557

  20. [20]

    Design optimization of microstrip antenna arrays using surrogate- based methodology,

    ——, “Design optimization of microstrip antenna arrays using surrogate- based methodology,” in2013 IEEE Antennas and Propagation Society International Symposium (APSURSI), Jul. 2013, pp. 1228–1229. [Online]. Available: https://ieeexplore.ieee.org/document/6711274

  21. [21]

    Phase-spacing optimization of linear microstrip antenna arrays by EM-based superposition models,

    ——, “Phase-spacing optimization of linear microstrip antenna arrays by EM-based superposition models,” in2014 Loughborough Antennas and Propagation Conference (LAPC), Nov. 2014, pp. 26–30. [Online]. Available: https://ieeexplore.ieee.org/document/6996312

  22. [22]

    Fast Full-Wave Synthesis of Printed Antenna Arrays Including Mutual Coupling,

    H. V . Bui, S. N. Jha, and C. Craeye, “Fast Full-Wave Synthesis of Printed Antenna Arrays Including Mutual Coupling,”IEEE Transactions on Antennas and Propagation, vol. 64, no. 12, pp. 5163–5171, Dec

  23. [23]

    Available: https://ieeexplore.ieee.org/document/7590001

    [Online]. Available: https://ieeexplore.ieee.org/document/7590001

  24. [24]

    Fast optimization of large antenna arrays on dielectric layers using surrogate Macro- Basis-Function representations,

    H. B. Van, S. N. Jha, and C. Craeye, “Fast optimization of large antenna arrays on dielectric layers using surrogate Macro- Basis-Function representations,” in2016 IEEE Symposium Series on Computational Intelligence (SSCI), Dec. 2016, pp. 1–4. [Online]. Available: https://ieeexplore.ieee.org/document/7849901

  25. [25]

    Array Synthesis in Terms of Characteristic Modes and Generalized Scattering Matrices,

    L. M ¨orlein and D. Manteuffel, “Array Synthesis in Terms of Characteristic Modes and Generalized Scattering Matrices,”IEEE Trans. Antennas Propag., vol. 73, no. 2, pp. 986–997, Feb. 2025. [Online]. Available: https://ieeexplore.ieee.org/document/10806475

  26. [26]

    Deembedding and Optimiza- tion of a Decoupling Structure Using a Modal Coupling Matrix,

    L. M ¨orlein, P. Gentner, and D. Manteuffel, “Deembedding and Optimiza- tion of a Decoupling Structure Using a Modal Coupling Matrix,” in2025 19th European Conference on Antennas and Propagation (EuCAP), Stockholm, 2025

  27. [27]

    On the Relation of Characteristic Modes of Different Conducting Structures,

    L. M ¨orlein and D. Manteuffel, “On the Relation of Characteristic Modes of Different Conducting Structures,” Dec. 2025. [Online]. Available: http://arxiv.org/abs/2509.09282

  28. [28]

    Manopt, a Matlab toolbox for optimization on manifolds,

    N. Boumal, B. Mishra, P.-A. Absil, and R. Sepulchre, “Manopt, a Matlab toolbox for optimization on manifolds,”Journal of Machine Learning Research, vol. 15, no. 42, pp. 1455–1459, 2014. [Online]. Available: https://www.manopt.org

  29. [29]

    A Generalized Expansion For Radiated And Scattered Fields,

    R. J. Garbacz, “A Generalized Expansion For Radiated And Scattered Fields,” Ph.D. dissertation, The Ohio State University, Columbus, Ohio, 1968

  30. [30]

    Theory of characteristic modes for conducting bodies,

    R. Harrington and J. Mautz, “Theory of characteristic modes for conducting bodies,”IEEE Trans. Antennas Propag., vol. 19, no. 5, pp. 622–628, Sep. 1971

  31. [31]

    Characteristic modes for dielectric and magnetic bodies,

    R. Harrington, J. Mautz, and Y . Chang, “Characteristic modes for dielectric and magnetic bodies,”IEEE Trans. Antennas Propag., vol. 20, no. 2, pp. 194–198, Mar. 1972

  32. [32]

    In-house Software CMC – Institute of Microwave and Wireless Systems – Leibniz University Hannover

    “In-house Software CMC – Institute of Microwave and Wireless Systems – Leibniz University Hannover.” [Online]. Available: https://www.hft.uni- hannover.de/en/forschung/projektbeispiele/characteristic-modes/in- house-software-cmc

  33. [33]

    On Characteristic Modes in the Presence of a Grounded Dielectric Slab,

    A. Mrochen, L. M ¨orlein, and D. Manteuffel, “On Characteristic Modes in the Presence of a Grounded Dielectric Slab,” in2025 19th European Conference on Antennas and Propagation (EuCAP), Mar. 2025, pp. 1–5

  34. [34]

    PMCHWT-Based Characteristic Mode Formulations for Material Bodies,

    P. Yl ¨a-Oijala and H. Wall ´en, “PMCHWT-Based Characteristic Mode Formulations for Material Bodies,”IEEE Transactions on Antennas and Propagation, vol. 68, no. 3, pp. 2158–2165, Mar. 2020. [Online]. Available: https://ieeexplore.ieee.org/document/8883187

  35. [35]

    Analysis of finite phase arrays of microstrip patches,

    A. Skrivervik and J. Mosig, “Analysis of finite phase arrays of microstrip patches,”IEEE Transactions on Antennas and Propagation, vol. 41, no. 8, pp. 1105–1114, Aug. 1993. [Online]. Available: https://ieeexplore.ieee.org/document/244652/

  36. [36]

    Block-Toeplitz fast integral equation solver for large finite periodic and partially periodic antenna arrays,

    E. Bleszynski, M. Bleszynski, and T. Jaroszewicz, “Block-Toeplitz fast integral equation solver for large finite periodic and partially periodic antenna arrays,” in2003 IEEE Topical Conference on Wireless Communication Technology, Oct. 2003, pp. 428–429. [Online]. Available: https://ieeexplore.ieee.org/document/1321590

  37. [37]

    Compact Multimode Multielement Antenna for Indoor UWB Massive MIMO,

    D. Manteuffel and R. Martens, “Compact Multimode Multielement Antenna for Indoor UWB Massive MIMO,”IEEE Trans. Antennas Propag., vol. 64, no. 7, pp. 2689–2697, Jul. 2016

  38. [38]

    Computing and Visualizing the Input Parameters of Arbitrary Planar Antennas via Eigenfunctions,

    B. Yang and J. J. Adams, “Computing and Visualizing the Input Parameters of Arbitrary Planar Antennas via Eigenfunctions,”IEEE Trans. Antennas Propag., vol. 64, no. 7, pp. 2707–2718, Jul. 2016. 14 Leonardo M ¨orleinLeonardo M ¨orlein (Graduate Student Member, IEEE) was born in 1994 in W¨urzburg, Germany. He received the B.Sc. and M.Sc. degrees in electric...