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Exploiting Movable Antennas in Multicast Communications
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This article investigates the integration of movable antennas (MAs) into multicast communication systems. By discretizing the motion of the MAs, a novel MA-assisted multicast transmission architecture is formulated. An alternating optimization (AO) algorithm based on successive convex approximation is proposed to optimize the transmit beamforming and antenna positions. To gain further insights, the two-user case is examined, and a closed-form expression for the optimal beamformer is derived. On this basis, a low-complexity greedy search algorithm is developed to optimize the placement of the MAs. Furthermore, under the assumption of a line-of-sight propagation environment, a branch-and-bound algorithm is designed to determine the globally optimal antenna configuration with reduced complexity compared to exhaustive search. Numerical simulations confirm that the proposed methods effectively enhance the achievable multicast rate.
Forward citations
Cited by 2 Pith papers
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Flexible Cylindrical Arrays with Movable Antennas for MISO System: Beamforming and Position Optimization
Movable antennas on a cylindrical array, optimized with fractional programming and a constrained Adam algorithm, are simulated to improve multi-user sum rate by up to 31% over fixed antennas.
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Energy Efficiency Maximization for Movable Antenna-Enhanced System Based on Statistical CSI
Movable antenna positions and transmit covariance are jointly optimized under statistical CSI via deterministic equivalents and alternating optimization, yielding modest energy efficiency gains over fixed arrays.
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