TY - JOUR
T1 - Movable Antenna Enabled Near-Field MU-MIMO Communication
AU - Pi, Xiangyu
AU - Zhu, Lipeng
AU - Mao, Haobin
AU - Xiao, Zhenyu
AU - Xia, Xiang Gen
AU - Zhang, Rui
N1 - Publisher Copyright:
© 2012 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Movable antenna (MA)
KW - antenna position optimization
KW - multiuser multiple-input multiple-output (MU-MIMO)
KW - near-field communication
UR - https://www.scopus.com/pages/publications/105012111220
U2 - 10.1109/LWC.2025.3592716
DO - 10.1109/LWC.2025.3592716
M3 - Article
AN - SCOPUS:105012111220
SN - 2162-2337
VL - 14
SP - 3319
EP - 3323
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
IS - 10
ER -