Movable antennas (MAs) represent a promising paradigm to enhance the spatial degrees of freedom of conventional multi-antenna systems by dynamically adapting the positions of antenna elements within a designated transmit area. In particular, by employing electro-mechanical MA drivers, the positions of the MA elements can be adjusted to shape a favorable spatial correlation for improving system performance. Although preliminary research has explored beamforming designs for MA systems, the intricacies of the power consumption and the precise positioning of MA elements are not well understood. Moreover, the assumption of perfect CSI adopted in the literature is impractical due to the significant pilot overhead and the extensive time to acquire perfect CSI. To address these challenges, we model the motion of MA elements through discrete steps and quantify the associated power consumption as a function of these movements. Furthermore, by leveraging the properties of the MA channel model, we introduce a novel CSI error model tailored for MA systems that facilitates robust resource allocation design. In particular, we optimize the beamforming and the MA positions at the BS to minimize the total BS power consumption, encompassing both radiated and MA motion power while guaranteeing a minimum required SINR for each user. To this end, novel algorithms exploiting the branch and bound (BnB) method are developed to obtain the optimal solution for perfect and imperfect CSI. Moreover, to support practical implementation, we propose low-complexity algorithms with guaranteed convergence by leveraging successive convex approximation (SCA). Our numerical results validate the optimality of the proposed BnB-based algorithms. Furthermore, we unveil that both proposed SCA-based algorithms approach the optimal performance within a few iterations, thus highlighting their practical advantages.
Movable-Antenna Relay Enhanced Multiuser Communications: Reinforcement Learning-Based Antenna Positioning and Power Allocation
School of Electronics and Information Engineering, Beihang University（北京航空航天大学电子信息工程学院）；School of Interdisciplinary Science, Beijing Institute of Technology（北京理工大学交叉科学研究院）
Movable-Antenna Enabled Robust Vehicular Consumer Networks Under Imperfect CSI
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；University of Chinese Academy of Sciences（中国科学院大学）；School of Automation and Intelligent Manufacturing, Southern University of Science and Technology（南方科技大学自动化与智能制造学院）；Department of Electrical and Electronic Engineering, Imperial College London（帝国理工学院电气电子工程系）；College of Computer Science and Software Engineering, Shenzhen University（深圳大学计算机科学与技术工程学院）
6D Movable Antenna for Internet of Vehicles: CSI-Free Dynamic Antenna Configuration
Jiangnan University（江南大学）；Nanchang University（南昌大学）；Tsinghua University（清华大学）；Brunel University（布鲁内尔大学）；Shanghai Jiao Tong University（上海交通大学）；the Hong Kong University of Science and Technology（香港科技大学）
6D Movable Antenna Enhanced Cell-free MIMO: Two-timescale Decentralized Beamforming and Antenna Movement Optimization
University of Electronic Science and Technology of China（电子科技大学）；King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学）；Beijing Institute of Technology（北京理工大学）；National University of Singapore（新加坡国立大学）；Kash Institute of Electronics and Information Industry（喀什电子信息产业研究院）
Unlocking the Potential of Movable Antennas: General and Practical Antenna Position Optimization
National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China（电子科技大学无线通信全国重点实验室）；Department of Electrical and Computer Engineering, National University of Singapore（新加坡国立大学电气与计算机工程系）
Exploiting Movable-Element STARS for Rate Splitting Multiple Access
Tongling University（铜陵大学）；University of Oulu（奥卢大学）；Queen’s University Belfast（贝尔法斯特女王大学）；Qilu Institute of Technology（齐鲁工业大学）；University of Luxembourg（卢森堡大学）
