Movable Antenna Assisted Dual-Polarized Multi-Cell Cooperative AirComp: An Alternating Optimization Approach
Mingyu Hu, Nan Liu, Wei Kang

TL;DR
This paper introduces a dual-polarized movable antenna framework for multi-cell AirComp, optimizing multiple parameters to significantly improve aggregation accuracy in wireless distributed systems.
Contribution
It proposes a novel joint optimization framework for dual-polarized movable antennas in AirComp, including an alternating algorithm and statistical-channel-based antenna placement methods.
Findings
Outperforms fixed and single-polarized antenna schemes in simulations.
Effectively minimizes mean squared error in multi-cell AirComp.
Demonstrates robustness under both instantaneous and statistical channel conditions.
Abstract
Over-the-air computation (AirComp) is a key enabler for distributed optimization, since it leverages analog waveform superposition to perform aggregation and thereby mitigates the communication bottleneck caused by iterative information exchange. However, AirComp is sensitive to wireless environment and conventional systems with fixed single-polarized base-station arrays cannot fully exploit spatial degrees of freedom while also suffering from polarization mismatch. To overcome these limitations, this paper proposes a multi-cell cooperative air-computation framework assisted by dual-polarized movable antennas (D-PMA), and formulates a mean squared error (MSE) minimization problem by jointly optimizing the combining matrix, polarization vectors, antenna positions, and user transmit coefficients. The resulting problem is highly nonconvex, so an alternating algorithm is developed in which…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Communication Technologies · Millimeter-Wave Propagation and Modeling
