Near-Field Channel Estimation for Movable Antenna Systems via Bidirectional Movement

Abstract

Movable antenna (MA) systems have emerged as a transformative approach in the area of wireless communications by enabling dynamic antenna repositioning within a local region. However, to achieve a high design flexibility, a sufficiently large movement region is generally required, which, however, introduces complex spherical wavefront effects. As such, this paper focuses on the near-field channel estimation problem for MA systems, aiming to acquire the channel state information at any position within the antenna movement region under the near-field field-response channel model. To this end, we propose a novel bidirectional movement strategy for joint estimation of both angular and distance parameters of multi-path components. Under this strategy, we develop an adaptive grid orthogonal matching pursuit algorithm that leverages geometric constraints between the bidirectional movement to resolve parameter ambiguities and mitigate grid mismatch effects. The algorithm incorporates adaptive refinement mechanisms, hierarchical search strategies, and convergence monitoring to ensure reliable parameter estimation. Simulation results demonstrate that the proposed approach significantly improves the parameter estimation accuracy in terms of normalized mean square error compared with conventional methods, particularly in the low signal-to-noise ratio regime.