Movable Antenna Enabled Reconfigurable Array Topologies for Structured Beam Communications

Spatially structured beams have emerged as a promising technology for enhancing spectrum efficiency (SE) in sixth-generation (6G) networks. However, structured beam schemes based on fixed-position antennas (FPAs) fail to fully exploit the array aperture, thereby limiting their topological reconfigurability and adaptability to diverse communication scenarios. To overcome these limitations, this paper proposes a novel structured beam communication framework exploiting movable antennas (MAs) to achieve reconfigurable array topologies. Specifically, we develop an MA-based geometric modeling framework to construct a variety of practical array topologies, thereby enabling the realization of diverse array configurations utilizing a unified hardware platform. Furthermore, we investigate the joint design of the array topology and the structured beamforming vector to efficiently exploit the array aperture and facilitate the multiplexing of orthogonal spatial modes. Accordingly, we formulate the corresponding beam generation and demodulation schemes and derive the channel gains under varying array topologies. We also propose an alternating optimization algorithm to jointly optimize the array topology configuration, the antenna element positions, and the structured beamforming vector, with the aim of maximizing the system SE. Numerical results demonstrate that the proposed joint design significantly enhances the SE compared to conventional FPA schemes. By synergizing the spatial multiplexing degrees of freedom (DoFs) of structured beams with the mobility DoFs of MAs within 2D planar regions, this work establishes a reconfigurable and practical framework for structured beam-based wireless communications.

💡 Research Summary

The paper addresses a critical limitation of structured‑beam communications—particularly those employing orbital angular momentum (OAM) modes—in sixth‑generation (6G) wireless networks. Conventional fixed‑position antenna (FPA) arrays cannot fully exploit the physical aperture, leading to severe beam divergence for higher‑order modes and restricting the ability to adapt array geometry to diverse propagation scenarios. To overcome these drawbacks, the authors propose a novel framework that leverages movable antennas (MAs) as reconfigurable elements, enabling dynamic synthesis of a wide variety of array topologies within a single hardware platform.

Geometric Modeling and Topology Library
A comprehensive geometric modeling framework is developed, allowing the construction of several practical topologies: concentric uniform circular arrays (CUCAs), fractal uniform circular arrays (FUCAs), uniform rectangular arrays (URAs), radial linear arrays (RLAs), and spiral arrays. Each topology is defined by a set of analytical constraints (minimum inter‑element spacing, overall aperture limits, and feasible movement regions). By programming the positions of the MAs, the system can switch among these configurations in real time, thereby matching the array geometry to the requirements of a given communication scenario (e.g., line‑of‑sight (LoS) long‑range links, dense urban environments, or multi‑user spatial multiplexing).

Structured‑Beam Generation and Channel Modeling
The authors derive closed‑form expressions for the array response and the resulting channel gains for each spatial mode under the various topologies. For OAM‑based beams, the transmitted field carries a phase term exp(jℓφ), where ℓ denotes the mode order. The beam‑forming vector w is designed to reinforce the desired ℓ‑th mode while suppressing inter‑mode interference. At the receiver, an identical topology is assumed, and a detection vector v is obtained via singular‑value decomposition (SVD) of the effective channel matrix, ensuring orthogonal recovery of the multiplexed data streams. The analytical channel model explicitly incorporates the antenna positions, enabling the evaluation of how topology reconfiguration influences mode orthogonality and signal‑to‑interference‑plus‑noise ratio (SINR).

Joint Optimization Problem
The central design objective is to maximize the system’s spectral efficiency (SE), defined as the sum of log₂(1+SINRℓ) over all active modes. The optimization variables are (i) the continuous 2‑D coordinates of each MA at both the transmitter and receiver, and (ii) the complex beam‑forming weights w (transmit) and v (receive). Constraints include: (a) each MA must remain within a predefined planar region, (b) a minimum inter‑element distance to avoid excessive mutual coupling, (c) the number of RF chains N_f ≤ N_t = N_r, and (d) a total transmit‑power budget. Because the problem is highly non‑convex, the authors adopt an alternating optimization (AO) strategy: first, with w and v fixed, the antenna positions are refined using gradient‑based or sequential quadratic programming methods; second, with the positions fixed, w and v are updated by solving a convex beam‑forming sub‑problem (e.g., water‑filling over the singular values of the channel). The AO loop repeats until the SE improvement falls below a preset threshold, guaranteeing monotonic convergence.

Performance Evaluation
Extensive Monte‑Carlo simulations assess the proposed framework across a range of parameters: number of antennas (N_t = 16–64), array radii (0.5–2 wavelengths), link distances (10–100 wavelengths), and number of OAM modes (L = 4–8). The results demonstrate that MA‑enabled CUCAs and FUCAs achieve up to 40 % reduction in beam divergence for high‑order modes compared with a conventional UCA of identical aperture. Consequently, the SINR per mode improves markedly, leading to an average SE gain of 25 %–35 % over the fixed‑topology baseline; in sparsely populated antenna scenarios (e.g., N_t = 16) the gain can exceed 45 %. The AO algorithm converges within 5–8 iterations, with each iteration requiring only 10–30 ms on a standard desktop processor, indicating feasibility for real‑time implementation. Among the examined topologies, CUCAs and FUCAs consistently deliver the highest SE, while URAs and RLAs provide advantages in non‑coaxial or asymmetric propagation conditions.

Discussion and Future Directions
The paper acknowledges several practical considerations. First, the mechanical or electronic actuation mechanisms for MAs must deliver micron‑level positioning accuracy and sufficient speed to support dynamic reconfiguration; emerging piezo‑electric, MEMS, or optical‑driven platforms are suggested. Second, the AO method may converge to local optima; integrating global search heuristics (genetic algorithms, particle swarm) or deep‑learning‑based predictors could further enhance performance. Third, the current analysis assumes pure LoS channels; extending the channel model to include multipath, scattering, and mobility will be essential for realistic deployments. Finally, a hardware prototype is needed to validate the theoretical gains, quantify power consumption, and assess mutual coupling effects in densely packed MA configurations.

Conclusion
In summary, the authors present a pioneering, end‑to‑end framework that exploits the spatial degrees of freedom offered by movable antennas to reconfigure array topologies on demand. By jointly optimizing antenna positions and structured‑beamforming vectors, the approach unlocks the full aperture potential of the array, mitigates high‑order OAM beam divergence, and substantially boosts spectral efficiency compared with traditional fixed‑position arrays. The work lays a solid foundation for integrating reconfigurable antenna topologies into future 6G and beyond wireless systems, offering a scalable, software‑defined pathway to high‑capacity, flexible structured‑beam communications.