Upward Spatial Coverage Recovery via Movable Antenna in Low-Altitude Communications

The rapid proliferation of unmanned aerial vehicle (UAV) applications imposes stringent requirements on continuous and reliable communication coverage in low-altitude airspace. Conventional cellular systems built upon fixed-position antennas (FPAs) are inherently constrained by static array geometries and limited mechanical degrees of freedom, which severely restrict their ability to adapt to highly dynamic three-dimensional (3D) propagation environments. Movable antenna (MA) technology has recently emerged as a promising paradigm to overcome these limitations by actively reconfiguring electromagnetic radiation characteristics through controllable antenna positioning and array orientation, thereby enabling flexible spatial coverage adaptation. To systematically quantify the airspace coverage capability of MA-enabled systems, this paper formulates a spatial coverage maximization problem over a discretized 3D voxel space. For each voxel, the received signal-to-noise ratio (SNR) is maximized via joint optimization of the MA’s 3D positions and beamforming matrices. To efficiently solve the resulting non-convex problem, a hybrid particle swarm optimization and simulated annealing framework is developed to search for high-quality antenna configurations. Simulation results demonstrate that the proposed MA design framework substantially outperforms conventional FPA-based schemes in terms of spatial coverage, achieving coverage rates of 26.8% and 29.65% for airspace below 300m and 600m, respectively. Moreover, further coverage enhancement can be attained by incorporating mechanical tilt adjustment, highlighting the strong potential of MA technology for reliable low-altitude communication coverage.

💡 Research Summary

The paper addresses the pressing need for continuous, reliable wireless coverage in the low‑altitude airspace (0–600 m) that is increasingly populated by unmanned aerial vehicles (UAVs). Conventional cellular base stations employ fixed‑position antennas (FPAs) whose radiation patterns are primarily downward‑oriented and whose mechanical tilt range is limited. Consequently, a “upward coverage gap” appears above the base stations, manifesting as cone‑shaped blind spots and inter‑site coverage holes, especially beyond 300 m altitude.

To overcome these intrinsic hardware constraints, the authors propose exploiting movable‑antenna (MA) technology. An MA can be repositioned and reoriented in three dimensions, thereby actively reshaping its radiation pattern and the resulting channel conditions. The core contribution is a systematic framework that quantifies the spatial‑coverage capability of an MA‑enabled system. The low‑altitude region is discretized into volumetric voxels; for each voxel the received signal‑to‑noise ratio (SNR) is computed, and the overall coverage metric is defined as the proportion of voxels whose SNR exceeds a predefined threshold.

Mathematically, the problem becomes a joint optimization over the MA’s 3‑D position vector and its beamforming matrix, with the objective of maximizing the voxel‑level coverage metric. This is a highly non‑convex problem because the SNR depends on both large‑scale path loss (which varies with the MA’s position) and small‑scale array gain (which depends on the beamforming weights). To solve it efficiently, the authors decompose the task into two sub‑problems. First, the MA’s position is optimized using a hybrid meta‑heuristic that combines Particle Swarm Optimization (PSO) for global exploration with Simulated Annealing (SA) for escaping local minima. Second, given a fixed MA location, the beamforming vectors are derived using Maximum Ratio Transmission (MRT), which maximizes the received power for each voxel while keeping computational complexity low.

Simulation settings employ a 3.5 GHz carrier, an 8 × 8 uniform planar array, and a realistic 3‑D propagation model that includes line‑of‑sight (LOS) and non‑LOS components. Three system configurations are compared: (i) a conventional FPA, (ii) a 3‑D movable‑antenna system (3DMA) that can reposition but has a fixed mechanical tilt, and (iii) a 4‑D system (4DMA) that adds mechanical up‑tilt capability. Results show that for altitudes ≤ 300 m, the 3DMA achieves a coverage rate of 26.8 %, roughly a 10 percentage‑point improvement over the FPA. For altitudes ≤ 600 m, the 4DMA reaches 29.65 % coverage, again outperforming the fixed‑antenna baseline by more than 12 percentage points. The inclusion of mechanical tilt further smooths coverage across the 400–600 m band, confirming that spatial degrees of freedom at the hardware level translate directly into measurable performance gains.

The paper’s key insights are: (1) voxel‑based SNR modeling provides a fine‑grained, altitude‑aware metric for upward coverage; (2) joint position‑beamforming optimization can be tractably solved with a PSO‑SA hybrid, delivering high‑quality solutions without exhaustive search; (3) MA technology fundamentally expands the design space beyond what is achievable with static arrays, enabling active compensation for tower‑top blind spots and inter‑site gaps.

Limitations are acknowledged. The study relies on simulations; practical issues such as the mechanical response time of the movable platform, power consumption, durability, and integration with existing base‑station infrastructure are not addressed. Moreover, multi‑cell coordination, real‑time UAV tracking, and dynamic traffic loads remain open research topics. Future work should involve hardware prototyping, real‑time control algorithms, and network‑level optimization to validate the concept in operational environments.

In summary, the work demonstrates that movable‑antenna systems, especially when combined with mechanical tilt control, can substantially recover upward spatial coverage in low‑altitude communications, offering a promising path toward seamless aerial‑terrestrial integrated networks.