Robust Movable Antenna Position Optimization Under Imperfect Channel Path Parameters

doi:10.12142/ZTECOM.202603006

ZTE Communications ›› 2026, Vol. 24 ›› Issue (3): 40-47.DOI: 10.12142/ZTECOM.202603006

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Robust Movable Antenna Position Optimization Under Imperfect Channel Path Parameters

Jia Qiaoran¹, Mei Weidong²(), Wei Xin², Chen Zhi², Ning Boyu²

^1.Glasgow College, University of Electronic Science and Technology of China, Chengdu 611731, China
^2.National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China, Chengdu 611731, China

Received:2026-06-10 Online:2026-09-20 Published:2026-09-20
About author:Jia Qiaoran received his BS degree in communication engineering from Glasgow College, University of Electronic Science and Technology of China. He is currently pursuing his MS degree with the School of Electronics, Peking University, China. His research interests include movable antennas and wireless communications. He was the co-recipient of the IEEE ComSoc SPCC Technical Committee Student Challenge and Video Contest Award in 2024.
Mei Weidong (wmei@uestc.edu.cn) received his BE degree in communication engineering and ME degree in communication and information systems from the University of Electronic Science and Technology of China (UESTC), in 2014 and 2017, respectively, and his PhD degree from the NUS Graduate School, National University of Singapore in 2021. He is currently a professor with UESTC. His research interests include reconfigurable MIMO, intelligent reflecting surfaces, wireless drone communications, and convex optimization techniques. Prof. Mei was the recipient of the Best Paper Award from the IEEE International Conference on Communications in 2021, and the Outstanding Master’s Thesis Award from the Chinese Institute of Electronics in 2017. He serves as an associate editor for the IEEE Transactions on Communications, IEEE Internet of Things Journal, IEEE Wireless Communications Letters and IEEE Open Journal of the Communications Society.
Wei Xin received his BS degree in communication engineering from Chongqing University of Posts and Telecommunications, China in 2023. He is currently pursuing his MS degree in information and communication engineering with the National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China. His research interests include movable antennas, wireless drone communications, and convex optimization. He was the co-recipient of the IEEE ComSoc SPCC Technical Committee Student Challenge and Video Contest Award in 2024.
Chen Zhi received his BE, ME, and PhD degrees in electrical engineering from the University of Electronic Science and Technology of China (UESTC) in 1997, 2000, and 2006, respectively. In April 2006, he joined the National Key Laboratory of Science and Technology on Communications, UESTC, where he has been a professor since 2013. He was a visiting scholar with the University of California, Riverside, USA from 2010 to 2011. He is also the Deputy Director of the Key Laboratory of Terahertz Technology, Ministry of Education of the People’s Republic of China. His current research interests include terahertz communication, 5G mobile communications, and tactile Internet. He serves as an editor of IEEE Transactions on Communications.
Ning Boyu received his BS degree in communication engineering from the Yingcai Honors College, University of Electronic Science and Technology of China (UESTC) in 2018, and his PhD degree from the National Key Laboratory of Wireless Communications, UESTC in 2023. From 2022 to 2023, he was a visiting student with the Department of Electrical and Computer Engineering, National University of Singapore. His research interests include terahertz communication, movable antennas, intelligent reflecting surfaces, massive MIMO, physical-layer security, and convex optimization.

Abstract

Abstract:

Movable antenna (MA) systems can reshape the wireless channel by repositioning antenna elements in a confined region, but most existing MA optimization methods depend on perfect channel state information (CSI). This paper studies robust joint transmit beamforming and antenna-position optimization for a downlink multiple-input single-output (MISO) MA system with imperfect CSI. Instead of treating CSI errors as unstructured channel perturbations, we introduce bounded uncertainties directly into physical multipath parameters, including path-gain amplitudes and angular parameters. The resulting worst-case signal-to-noise ratio (SNR) design is approximated through discrete sampling and a harmonic-mean surrogate that penalizes weak channel realizations. An alternating optimization algorithm is then developed, where transmit beamforming is updated on the complex sphere manifold, and antenna positions are optimized via a sequential grid search. Simulation results show that the proposed robust design yields higher SNR performance than non-robust designs and the fixed-position antenna (FPA) baseline.

Key words: alternating optimization, harmonic mean, imperfect channel state information, movable antenna, robust optimization

Jia Qiaoran, Mei Weidong, Wei Xin, Chen Zhi, Ning Boyu. Robust Movable Antenna Position Optimization Under Imperfect Channel Path Parameters[J]. ZTE Communications, 2026, 24(3): 40-47.

Figures/Tables 7

Figure 1 Downlink MA-enhanced communication system

Figure 2 Robust joint beamforming and MA-position optimization flow

Table 1 Summary of simulation parameters

Parameter	Default Value
Carrier frequency ( $f c)$	$5 G H z$
Wavelength ( $λ)$	$0.06 m$
Default number of MAs ( $N)$	4
Number of paths ( $L)$	3
BS-user distance ( $d)$	$50 m$
Path-loss exponent ( $α)$	$2.8$
Transmit region ( $A × A)$	$4 λ × 4 λ$
Minimum spacing ( $D m i n)$	$λ / 2$
Transmit power ( $P t)$	$46 d B m$
Noise power ( $σ 2)$	$- 44 d B m$

Table 1 Summary of simulation parameters

Parameter	Default Value
Carrier frequency ( $f c)$	$5 G H z$
Wavelength ( $λ)$	$0.06 m$
Default number of MAs ( $N)$	4
Number of paths ( $L)$	3
BS-user distance ( $d)$	$50 m$
Path-loss exponent ( $α)$	$2.8$
Transmit region ( $A × A)$	$4 λ × 4 λ$
Minimum spacing ( $D m i n)$	$λ / 2$
Transmit power ( $P t)$	$46 d B m$
Noise power ( $σ 2)$	$- 44 d B m$

Figure 3 Convergence behavior of the proposed alternating optimization algorithm

Table 2 Summary of the proposed method and benchmark schemes

Scheme	CSI Assumption	Antenna Type	Design Principle
Proposed robust MA	Imperfect CSI	Movable	Harmonic-mean robust AO
Perfect-CSI+MA	Perfect CSI	Movable	Graph-DP with true CSI
Imperfect-CSI+MA	Imperfect CSI	Movable	Graph-DP with estimated CSI
Imperfect-CSI+FPA	Imperfect CSI	Fixed	MRT with estimated CSI

Figure 4 Average actual received SNR versus CSI uncertainty level

Figure 5 Average actual received SNR versus the number of transmit antennas at Δ=0.5

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Robust Movable Antenna Position Optimization Under Imperfect Channel Path Parameters

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