The paper proposes a hybrid near-far field channel model for 6D movable antennas, a directional-sparsity-based channel estimator, and a deep reinforcement learning algorithm for joint position, rotation, and beamforming design, with simulation gains over fixed and fluid antenna systems.
Channel estimation for extremely large-scale massive MIMO systems,
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Hybrid Near-Far Field 6D Movable Antenna Design Exploiting Directional Sparsity and Deep Learning
The paper proposes a hybrid near-far field channel model for 6D movable antennas, a directional-sparsity-based channel estimator, and a deep reinforcement learning algorithm for joint position, rotation, and beamforming design, with simulation gains over fixed and fluid antenna systems.