Movable Antenna Enabled Near-Field MU-MIMO Communication

• Published in: IEEE wireless communications letters p. 1
• Main Authors: Pi, Xiangyu, Zhu, Lipeng, Mao, Haobin, Xiao, Zhenyu, Xia, Xiang-Gen, Zhang, Rui
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: Antenna arrays; antenna position optimization; Antennas; Matching pursuit algorithms; MIMO; Movable antenna (MA); multiuser multiple-input multiple-output (MU-MIMO); near-field communication; Optimization; Precoding; Sparse matrices; Transforms; Transmitting antennas; Vectors
• ISSN: 2162-2337; 2162-2345
• DOI: 10.1109/LWC.2025.3592716

This letter investigates movable antenna (MA)-enabled near-field multiuser multiple-input multiple-output (MU-MIMO) systems, in which the base station (BS) equipped with an MA array serves multiple users equipped with fixed-position antenna (FPA) arrays. First, we present the near-field channel model to characterize channel variations with different positions of the MAs in a large moving region. Then, we aim to maximize the weighted sum-rate (WSR) of users by jointly optimizing the antenna position vector (APV) and precoding matrix at BS, subject to the constraints on antenna movement and maximum transmit power. To address the formulated challenging optimization problem, we discretize the feasible antenna moving region into a discrete-position set, and transform the problem into a sparse signal recovery framework. Next, based on the orthogonal matching pursuit (OMP) method, the suboptimal MAs' positions are selected from the discrete-position set and the precoding matrix is simultaneously updated in closed-form to align with the APV changes. Simulation results show that the proposed MA-enabled system can significantly improve near-field MIMO channel conditions and enhance multi-stream transmission via antenna position optimization, achieving substantial performance gains over conventional FPA-based schemes.