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Movable Antenna-Aided Hybrid Beamforming for Multi-User Communications
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In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within different local regions. To maximize the system sum rate, we jointly optimize the digital beamformer, analog beamformer, and positions of subarrays, under the constraints of unit modulus, finite movable regions, and power budget. Due to the non-concave/non-convex objective function/constraints, as well as the highly coupled variables, the formulated problem is challenging to solve. By employing fractional programming, we develop an alternating optimization framework to solve the problem via a combination of Lagrange multipliers, penalty method, and gradient descent. Numerical results reveal that the proposed MA-aided hybrid beamforming scheme significantly improves the sum rate compared to its fixed-position antenna (FPA) counterpart. Moreover, with sufficiently large movable regions, the proposed scheme with sub-connected MA arrays even outperforms the fully-connected FPA array.
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Cited by 2 Pith papers
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6DMA-Aided Hybrid Beamforming with Joint Antenna Position and Orientation Optimization
A polarization-aware channel model and fractional programming framework for sub-connected 6DMA hybrid beamforming achieves higher simulated sum rates than fixed, position-only, and orientation-only baselines.
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Throughput Maximization for Movable Antenna Systems with Movement Delay Consideration
A delay-aware throughput maximization framework for movable-antenna downlinks, with SCA and SDR algorithms that outperform fixed-position and delay-ignorant schemes in simulations.
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