Multiuser Communications With Movable-Antenna Base Station: Joint Antenna Positioning, Receive Combining, and Power Control

• Published in: IEEE transactions on wireless communications Vol. 23; no. 12; pp. 19744 - 19759
• Main Authors: Xiao, Zhenyu, Pi, Xiangyu, Zhu, Lipeng, Xia, Xiang-Gen, Zhang, Rui
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: antenna positioning; Antennas; Channel estimation; Iterative algorithms; MIMO communication; Movable antenna (MA); Multiplexing; Optimization; Particle swarm optimization; particle swarm optimization (PSO); Power control; Radio frequency; Receiving antennas; Transceivers; Transmitting antennas; Uplink; uplink communication; Uplinking; Vectors
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2024.3486320

Movable antenna (MA) is an innovative technology that facilitates the repositioning of antennas within the transmitter/receiver area to enhance channel conditions and communication performance. This paper proposes a new base station (BS) architecture employing multiple MAs for improving the multiuser network performance. First, the uplink multiple access channel (MAC) is modeled to capture the characteristics of the variation of wireless channels caused by the movement of MAs at the BS. Subsequently, we propose to maximize the minimum achievable rate among multiple users for MA-aided multiuser uplink transmissions by joint optimization of the MAs' positions, their receive combining at the BS, and the transmit power of users, subject to the MAs' positions-related constraints and the maximum transmit power of each user. To tackle this highly non-convex max-min fairness problem, we propose a two-loop iterative algorithm based on the particle swarm optimization (PSO). Specifically, the outer-loop updates the positions of a set of particles, where each particle's position corresponds to one realization of the antenna position vector (APV) of all MAs. The inner-loop conducts the fitness evaluation for each particle, determining the max-min achievable rate for multiple users based on the current APV. Therein, for given APV, the receive combining matrix at the BS and the transmit power for each user are optimized using the block coordinate descent (BCD) technique. To further reduce the computational complexity, we develop an alternating optimization (AO)-based algorithm via iteratively updating the APV, combining matrix, and transmit power. Finally, extensive simulations demonstrate that the antenna position optimization for MAs-aided BSs can significantly improve the rate performance as compared to conventional BSs with fixed-position antennas (FPAs).