pith. sign in

arxiv: 2606.31466 · v2 · pith:R6KHNRN3new · submitted 2026-06-30 · 💻 cs.IT · math.IT

Antenna Orientation Optimization for Rotatable Antenna-Enabled ISAC Systems

Qingjie Wu , Beixiong Zheng , Guangchi Zhang , Robert Schober This is my paper

Pith reviewed 2026-07-03 22:11 UTC · model grok-4.3

classification 💻 cs.IT math.IT
keywords rotatable antennaISACantenna orientationbeamforming optimizationalternating optimizationsensing echo power
0
0 comments X

The pith

Rotatable antennas at the base station can be oriented to maximize minimum sensing echo power in ISAC systems while satisfying user communication rates.

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

This paper explores deploying an array of rotatable antennas at the base station for integrated sensing and communication. The goal is to optimize antenna orientations along with beamforming to maximize the weakest sensing echo in a region, while keeping communication rates above thresholds for multiple users. In the special case of one user and a point target far away, all antennas should point the same way, and a closed-form solution gives the best direction. For the general case, the authors develop an alternating optimization procedure that cycles through beamforming, signal covariance, and antenna pointing. Numerical tests show this approach beats systems with fixed antennas or only array-level rotation.

Core claim

The paper shows that by allowing individual rotation of each antenna in the array, the ISAC system gains extra degrees of freedom that can be exploited through joint optimization of orientations and signals to achieve higher sensing performance under communication constraints, with a closed-form solution available when users and targets are in the far field.

What carries the argument

Alternating optimization of transmit beamforming, probing signal covariance matrix, and individual RA pointing vectors.

If this is right

  • Simulation results show significantly higher minimum echo signal power than benchmark schemes.
  • The closed-form solution provides optimal identical orientations for far-field single-user point-target cases.
  • The AO algorithm converges to better solutions than array-wise rotation optimization.

Where Pith is reading between the lines

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

  • Similar optimization could apply to other flexible antenna architectures like movable antennas.
  • Performance gains might diminish in near-field scenarios where the far-field assumption fails.
  • Extending to dynamic targets or mobile users would require additional tracking mechanisms.

Load-bearing premise

The communication user and sensing target lie in the far-field region, which allows the optimal antenna orientations to be identical and admits a closed-form solution.

What would settle it

A simulation or measurement in the near-field region where the derived closed-form pointing vector fails to maximize the minimum echo power.

Figures

Figures reproduced from arXiv: 2606.31466 by Beixiong Zheng, Guangchi Zhang, Qingjie Wu, Robert Schober.

Figure 1
Figure 1. Figure 1: An RA-enabled ISAC system for multi-user communication and [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Illustration of the considered sector and conical surface of RA [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Echo signal power of the proposed RA-enabled ISAC system versus [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 6
Figure 6. Figure 6: Minimum echo signal power of different systems versus the required [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 5
Figure 5. Figure 5: Achievable rate of different ISAC systems versus the target’s azimuth [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 7
Figure 7. Figure 7: Minimum echo signal power of different systems versus the maximum [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Minimum echo signal power of different systems versus the antenna [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
read the original abstract

Non-fixed flexible antenna architectures, such as fluid antenna system (FAS), movable antenna (MA), and pinching antenna, have garnered significant interest in recent years. In this paper, we deploy a rotatable antenna (RA) array at the base station (BS) to improve the integrated sensing and communication (ISAC) performance by exploiting the additional spatial degrees of freedom (DoFs) introduced by antenna rotation. To enhance the sensing performance over an extended region containing a potential target while meeting the communication requirements of multiple users, we aim to maximize the minimum echo signal power within the sensing region, subject to required minimum communication rates of the users. For the special case of a single user and a point target, we show that the optimal orientation of all RAs is identical when both the communication user and the sensing target are located in the far-field region, and then derive a closed-form solution for the optimal RA pointing vector. For the general multi-user and extended-target case, we propose an alternating optimization (AO) algorithm that alternately optimizes the transmit beamforming for communication, the covariance matrix of the probing signal, and the pointing vectors of the RAs in an iterative manner. Simulation results demonstrate that the proposed RA-enabled ISAC system can significantly outperform various benchmark schemes, including systems with array-wise rotation optimization and fixed antenna orientation.

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

0 major / 3 minor

Summary. The manuscript presents an approach to optimize the orientation of rotatable antennas (RAs) in an ISAC system at the base station. The goal is to maximize the minimum echo signal power in a sensing region subject to communication rate constraints for multiple users. For the special case of single user and point target in the far-field, all RAs have the same optimal orientation, for which a closed-form solution is derived. For the general case, an alternating optimization algorithm is proposed that iterates over transmit beamforming, probing signal covariance matrix, and RA pointing vectors. Simulation results show that the proposed system outperforms benchmarks including array-wise rotation optimization and fixed antenna orientation.

Significance. If valid, the paper demonstrates the value of antenna rotation as an additional degree of freedom in ISAC systems, providing both a closed-form solution in a special case and a practical AO algorithm for the general case. The simulation results supporting outperformance over several benchmarks add to the evidence for the benefits of flexible antenna architectures. The derivation under standard far-field assumptions aligns with existing literature without introducing circularity.

minor comments (3)
  1. [Abstract] Consider including quantitative performance improvements (e.g., percentage gains in echo power) in the abstract to better highlight the results.
  2. [Simulation Results] The figures would benefit from error bars or multiple Monte Carlo runs to indicate variability in the reported outperformance.
  3. Check for consistent use of notation for the pointing vectors and channel models throughout the paper.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive assessment of the manuscript, the accurate summary of its contributions, and the recommendation for minor revision. No major comments were provided in the report.

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper derives a closed-form solution for the single-user point-target case from the standard far-field assumption and proposes an alternating optimization algorithm for the general case using conventional convex optimization steps on beamforming and covariance matrices. No load-bearing step reduces by construction to a fitted parameter, self-defined quantity, or self-citation chain; the simulation outperformance claims rest on external benchmarks rather than internal redefinitions. The derivation chain is self-contained against standard ISAC channel models.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work relies on standard far-field wireless channel models and convex optimization techniques from the broader ISAC literature; no new entities are postulated.

axioms (1)
  • domain assumption Far-field approximation holds for user and target locations in the special case
    Invoked to obtain identical optimal orientations and the closed-form pointing vector.

pith-pipeline@v0.9.1-grok · 5770 in / 1257 out tokens · 34796 ms · 2026-07-03T22:11:18.620314+00:00 · methodology

Review history (2 revisions) →

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 · 2 internal anchors

  1. [1]

    Integrated sensing and communications: Toward dual-functional wire- less networks for 6G and beyond,

    F. Liu, Y . Cui, C. Masouros, J. Xu, T. X. Han, Y . C. Eldar, and S. Buzzi, “Integrated sensing and communications: Toward dual-functional wire- less networks for 6G and beyond,”IEEE J. Sel. Areas Commun., vol. 40, no. 6, pp. 1728–1767, Jun. 2022

    work page 2022

  2. [2]

    6G wire- less communication systems: Applications, requirements, technologies, challenges, and research directions,

    M. Z. Chowdhury, M. Shahjalal, S. Ahmed, and Y . M. Jang, “6G wire- less communication systems: Applications, requirements, technologies, challenges, and research directions,”IEEE Open J. Commun. Soc., vol. 1, pp. 957–975, Aug. 2020

    work page 2020

  3. [3]

    A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,

    W. Saad, M. Bennis, and M. Chen, “A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,”IEEE Network, vol. 34, no. 3, pp. 134–142, May 2020

    work page 2020

  4. [4]

    A survey on fundamental limits of integrated sensing and communication,

    A. Liu, Z. Huang, M. Liet al., “A survey on fundamental limits of integrated sensing and communication,”IEEE Commun. Surveys Tuts., vol. 24, no. 2, pp. 994–1034, 2nd Quart., 2022

    work page 2022

  5. [5]

    MIMO integrated sensing and commu- nication: CRB-rate tradeoff,

    H. Hua, T. X. Han, and J. Xu, “MIMO integrated sensing and commu- nication: CRB-rate tradeoff,”IEEE Trans. Wireless Commun., vol. 23, no. 4, pp. 2839–2854, Apr. 2024

    work page 2024

  6. [6]

    A tutorial on fluid antenna system for 6G networks: Encompassing communication theory, optimization methods and hardware designs,

    W. K. New, K.-K. Wong, H. Xuet al., “A tutorial on fluid antenna system for 6G networks: Encompassing communication theory, optimization methods and hardware designs,”IEEE Commun. Surveys Tuts., vol. 27, no. 4, pp. 2325–2377, Aug. 2025

    work page 2025

  7. [7]

    Movable antennas for wireless commu- nication: Opportunities and challenges,

    L. Zhu, W. Ma, and R. Zhang, “Movable antennas for wireless commu- nication: Opportunities and challenges,”IEEE Commun. Mag., vol. 62, no. 6, pp. 114–120, Jun. 2024

    work page 2024

  8. [8]

    A tutorial on six-dimensional mov- able antenna for 6G networks: Synergizing positionable and rotatable antennas,

    X. Shao, W. Mei, C. Youet al., “A tutorial on six-dimensional mov- able antenna for 6G networks: Synergizing positionable and rotatable antennas,”IEEE Commun. Surveys Tuts., vol. 28, pp. 3666–3709, Aug. 2025

    work page 2025

  9. [9]

    Rotatable antenna enabled wireless communication and sensing: Opportunities and challenges,

    B. Zheng, T. Ma, C. You, J. Tang, R. Schober, and R. Zhang, “Rotatable antenna enabled wireless communication and sensing: Opportunities and challenges,”IEEE Wireless Commun., Early Access, Oct. 2025

    work page 2025

  10. [10]

    Fluid antenna-assisted ISAC systems,

    L. Zhou, J. Yao, M. Jin, T. Wu, and K.-K. Wong, “Fluid antenna-assisted ISAC systems,”IEEE Wireless Commun. Lett., vol. 13, no. 12, pp. 3533– 3537, Dec. 2024

    work page 2024

  11. [11]

    Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning,

    C. Wang, G. Li, H. Zhang, K.-K. Wong, Z. Li, D. W. K. Ng, and C.-B. Chae, “Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning,”IEEE Trans. Wireless Commun., vol. 23, no. 9, pp. 10 879–10 894, Sep. 2024

    work page 2024

  12. [12]

    Antenna position and beamforming optimization for movable antenna enabled ISAC: Optimal solutions and efficient algorithms,

    L. Chen, M.-M. Zhao, M.-J. Zhao, and R. Zhang, “Antenna position and beamforming optimization for movable antenna enabled ISAC: Optimal solutions and efficient algorithms,”IEEE Trans. Signal Process., vol. 73, Jul. 2025

    work page 2025

  13. [13]

    Movable antenna- aided near-field integrated sensing and communication,

    J. Ding, Z. Zhou, X. Shao, B. Jiao, and R. Zhang, “Movable antenna- aided near-field integrated sensing and communication,”IEEE Trans. Wireless Commun., vol. 25, pp. 493–508, 2026

    work page 2026

  14. [14]

    Movable antenna enhanced wireless sensing via antenna position optimization,

    W. Ma, L. Zhu, and R. Zhang, “Movable antenna enhanced wireless sensing via antenna position optimization,”IEEE Trans. Wireless Com- mun., vol. 23, no. 11, pp. 16 575–16 589, Nov. 2024

    work page 2024

  15. [15]

    Movable-antenna array empowered ISAC systems for low-altitude economy,

    Z. Kuang, W. Liu, C. Wang, Z. Jin, J. Ren, X. Zhang, and Y . Shen, “Movable-antenna array empowered ISAC systems for low-altitude economy,” inProc. IEEE/CIC Int. Conf. Commun. China (ICCC Work- shops), Hangzhou, China, Aug. 2024, pp. 776–781

    work page 2024

  16. [16]

    Exploiting six-dimensional mov- able antenna for wireless sensing,

    X. Shao, R. Zhang, and R. Schober, “Exploiting six-dimensional mov- able antenna for wireless sensing,”IEEE Wireless Commun. Lett., vol. 14, no. 2, pp. 265–269, Feb. 2025

    work page 2025

  17. [17]

    UA V-enabled passive 6D movable antenna for ISAC: Joint location, orientation, and reflection optimization,

    P. Wang, Y . Xue, W. Mei, J. Fang, and R. Zhang, “UA V-enabled passive 6D movable antenna for ISAC: Joint location, orientation, and reflection optimization,”IEEE Wireless Commun. Lett., vol. 14, no. 12, pp. 3982– 3986, Dec. 2025

    work page 2025

  18. [18]

    6DMA enhanced wireless network with flexible antenna position and rotation: Opportunities and challenges,

    X. Shao and R. Zhang, “6DMA enhanced wireless network with flexible antenna position and rotation: Opportunities and challenges,”IEEE Commun. Mag., vol. 63, no. 4, pp. 121–128, Apr. 2025

    work page 2025

  19. [19]

    Modeling and optimization for rotatable antenna enabled wireless communication,

    Q. Wu, B. Zheng, T. Ma, and R. Zhang, “Modeling and optimization for rotatable antenna enabled wireless communication,” inProc. IEEE Int. Conf. Commun. (ICC), Montreal, Canada, Jun. 2025, pp. 1055–1060

    work page 2025

  20. [20]

    Rotatable antenna enabled wireless communication: Modeling and optimization,

    B. Zheng, Q. Wu, T. Ma, and R. Zhang, “Rotatable antenna enabled wireless communication: Modeling and optimization,”IEEE Trans. Commun., vol. 74, pp. 6825–6842, Mar. 2026

    work page 2026

  21. [21]

    Rotatable antenna-empowered wireless networks: A tutorial,

    B. Zheng, Q. Wu, X. Xionget al., “Rotatable antenna-empowered wireless networks: A tutorial,”arXiv preprint arXiv:2603.25559, Mar. 2026

    work page arXiv 2026

  22. [22]

    Ro- tatable antenna-enabled secure wireless communication,

    L. Dai, B. Zheng, Q. Wu, C. You, R. Schober, and R. Zhang, “Ro- tatable antenna-enabled secure wireless communication,”IEEE Wireless Commun. Lett., vol. 14, no. 11, pp. 3440–3444, Nov. 2025

    work page 2025

  23. [23]

    Rotatable antenna enabled spectrum sharing: Joint antenna orientation and beam- forming design,

    X. Peng, Q. Wu, Z. Zheng, W. Chen, Y . Zhu, and Y . Gao, “Rotatable antenna enabled spectrum sharing: Joint antenna orientation and beam- forming design,”IEEE Trans. Wireless Commun., vol. 25, pp. 15 660– 15 674, Apr. 2026

    work page 2026

  24. [24]

    Ro- tatable antenna-enabled spectrum sharing in cognitive radio systems,

    Y . Tan, B. Zheng, Y . Fang, D. W. Kwan Ng, J. Xu, and R. Zhang, “Ro- tatable antenna-enabled spectrum sharing in cognitive radio systems,” IEEE Wireless Commun. Lett., vol. 15, pp. 1732–1736, Jan. 2026

    work page 2026

  25. [25]

    Rotatable Antenna-Enhanced Cell-Free Communication

    K. Pan, B. Zheng, Y . Tan, E. Bj ¨ornson, R. Schober, and R. Zhang, “Rotatable antenna-enhanced cell-free communication,”arXiv preprint arXiv:2512.04742, 2025

    work page internal anchor Pith review Pith/arXiv arXiv 2025

  26. [26]

    Cell-Free MIMO with Rotatable Antennas: When Macro-Diversity Meets Antenna Directivity

    X. Peng, Q. Wu, Z. Zheng, Y . Zhu, W. Chen, P. Huang, Y . Gao, and H. Wang, “Cell-free MIMO with rotatable antennas: When macro- diversity meets antenna directivity,”arXiv preprint arXiv:2601.16543, May 2026

    work page internal anchor Pith review Pith/arXiv arXiv 2026

  27. [27]

    Rotatable antenna enhanced integrated sensing and communication,

    Q. Wu, B. Zheng, C. You, and J. Tang, “Rotatable antenna enhanced integrated sensing and communication,” inProc. IEEE GLOBECOM Workshops (GC Wkshps), Taipei, Taiwan, Dec. 2025, pp. 1–6

    work page 2025

  28. [28]

    Intelligent rotatable antenna for integrated sensing, communication, and computation: Challenges and opportunities,

    X. Xiong, B. Zheng, W. Wu, W. Zhu, M. Wen, S. Lin, and Y . Zeng, “Intelligent rotatable antenna for integrated sensing, communication, and computation: Challenges and opportunities,”IEEE Wireless Commun., vol. 33, no. 1, pp. 173–180, 2026

    work page 2026

  29. [29]

    Rotatable antennas for integrated sensing and communications,

    C. Zhou, C. You, B. Zheng, X. Shao, and R. Zhang, “Rotatable antennas for integrated sensing and communications,”IEEE Wireless Commun. Lett., vol. 14, no. 9, pp. 2838–2842, Sep. 2025

    work page 2025

  30. [30]

    Rotatable antennas for near-field integrated sensing and communication,

    Y . Zhang, H. C. So, D. Niyato, and C. Masouros, “Rotatable antennas for near-field integrated sensing and communication,”IEEE Trans. Wireless Commun., vol. 25, pp. 10 986–11 001, Jan. 2026

    work page 2026

  31. [31]

    Rotatable array-enabled multi-bs cooperative ISAC transmit beampattern design,

    K. Qu, H. Li, C. Sun, W. Zhang, S. Guo, and H. Zhang, “Rotatable array-enabled multi-bs cooperative ISAC transmit beampattern design,” IEEE Trans. V eh. Technol., vol. 74, no. 9, pp. 14 775–14 780, Sep. 2025

    work page 2025

  32. [32]

    C. A. Balanis,Antenna Theory: Analysis and Design. John wiley & sons, 2015

    work page 2015

  33. [33]

    Efficient channel estimation for rotatable antenna-enabled wireless communication,

    X. Xiong, B. Zheng, W. Wu, X. Shao, L. Dai, M.-M. Zhao, and J. Tang, “Efficient channel estimation for rotatable antenna-enabled wireless communication,”IEEE Wireless Commun. Lett., vol. 14, no. 11, pp. 3719–3723, Nov. 2025

    work page 2025

  34. [34]

    Boyd and L

    S. Boyd and L. Vandenberghe,Convex Optimization. Cambridge, U.K.: Cambridge Univ. Press, 2004

    work page 2004

  35. [35]

    Quaternions, interpolation and animation,

    E. B. Dam, M. Koch, and M. Lillholm, “Quaternions, interpolation and animation,” 1998

    work page 1998

  36. [36]

    Joint transmit beamforming for multiuser MIMO communications and MIMO radar,

    X. Liu, T. Huang, N. Shlezinger, Y . Liu, J. Zhou, and Y . C. Eldar, “Joint transmit beamforming for multiuser MIMO communications and MIMO radar,”IEEE Trans. Signal Process., vol. 68, pp. 3929–3944, Jul. 2020

    work page 2020

  37. [37]

    R. A. Horn and C. R. Johnson,Matrix Analysis. Cambridge, U.K.: Cambridge Univ. Press, 1985

    work page 1985

  38. [38]

    Convex optimization: Algorithms and complexity,

    S. Bubeck, “Convex optimization: Algorithms and complexity,”F ound. Trends Mach. Learn., vol. 8, no. 3-4, pp. 231–357, 2015

    work page 2015